Month: September 2022
MMS • Anthony Alford
Article originally posted on InfoQ. Visit InfoQ
Researchers from Microsoft’s Natural Language Computing (NLC) group announced the latest version of Bidirectional Encoder representation from Image Transformers: BEiT-3, a 1.9B parameter vision-language AI model. BEiT-3 models images as another language and achieves state-of-the-art performance on a wide range of downstream tasks.
The model and experiments were described in a paper published on arXiv. The key idea in BEiT-3 is to model images as another language (which the authors call “Imglish”); this allows the model to be pretrained using only the masked language modeling (MLM) objective, and the training process can therefore be scaled up more easily. This unified architecture allows BEiT-3 to support a wide range of downstream tasks: in evaluation experiments, the model set new state-of-the-art performance records on several benchmarks, including semantic segmentation, cross-modal retrieval, and visual question answering. According to the Microsoft team:
BEIT-3 is simple and effective, and is a promising direction for scaling up multimodal foundation models. For future work, we are working on pretraining multilingual BEIT-3 and including more modalities (e.g., audio) in BEIT-3 to facilitate the cross-lingual and cross-modality transfer, and advance the big convergence of large-scale pretraining across tasks, languages, and modalities.
Since its original publication in 2017, the Transformer model has become the preferred architecture for many natural language processing (NLP) tasks. This led to many researchers adopting the Transformer for vision tasks, and then combining both NLP and vision in a single model. However, these multi-modal architectures often maintain separate encoder modules for the different inputs and require multiple pretraining objectives beyond the standard MLM objective.
By contrast, BEiT-3 uses the Multiway Transformer architecture, which uses a shared self-attention module for both image and text data. The attention head output is then routed to a modality-specific feedforward “expert” module. Because the model pretraining uses only the MLM objective, a smaller batch size can be used, which reduces the amount of GPU memory required to process a training batch.
BEiT-3 was pretrained on several publicly-available text and image datasets, including ImageNet, COCO, and the contents of Wikipedia; overall the data contained 160GB of text-only documents, 14M images, and 21M text-image pairs. The team evaluated the model on several vision and vision-language benchmark tasks, including: semantic segmentation on the ADE20K; object detection, instance segmentation, image captioning, and retrieval on COCO; retrieval on Flickr30K; and visual question answering on VQAv2. BEiT-3 outperformed previous models on most of the tasks; a full list of results is available on Papers with Code.
Large vision-language models are an active research topic. InfoQ covered Google’s Vision Transformer (ViT) in 2021 and DeepMind’s Flamingo model earlier this year. In a Twitter discussion about BEiT-3, Google researcher and ViT co-author Lucas Beyer praised the BEiT-3 team, saying:
Impressive work, congrats! Happy to see someone else successfully training a ViT-G…and such good results on only 35M images does make the masked modeling task appealing!
Microsoft recently released the code and model weights for BEiT v2 on GitHub, and co-author Li Dong said on Twitter that BEiT-3 should be open-sourced soon.
MMS • A N M Bazlur Rahman
Article originally posted on InfoQ. Visit InfoQ
Jakarta EE 10, released on September 22, 2022, is the third major and fourth overall release of Jakarta EE by the Jakarta EE Working Group since Oracle donated Java EE 8 to the Eclipse Foundation in 2017. This release aims to deliver a set of coordinated specifications for building modernized, simplified, and lightweight cloud-native Java applications across the spectrum of Jakarta EE technologies, such as the Jakarta EE Platform, Web, and the new Core profiles.
The new Core Profile defines a subset of the Jakarta EE specifications geared toward microservices development, smaller runtimes, and ahead-of-time (AOT) compilation.
Java SE 11 is the new baseline runtime supported by Jakarta EE-compatible implementations. However, developers can also develop and deploy the Jakarta EE application on Java 17, which is the most current LTS release. This leads to the opportunity to build modularized applications (introduced in Java 9) and offers improved integration across component APIs.
Jakarta EE 10 provides new functionality in over 20 component specifications. For example:
- A new CDI-Lite specification is introduced in Jakarta Context and Dependency Injection (CDI) 4.0, allowing a reflection-free programming model while maximizing resilience, testability, and maintainability in comparison to conventional approaches.
- Jakarta RESTful Web Services 3.1 standardizes a Java SE Bootstrap API, which allows REST services outside of the Jakarta EE environment, e.g. unit tests, integration tests, etc. This specification also standardizes the multipart form data, which has been missing for many years, and developers needed either Servlets or a vendor-specific REST API to handle the multipart media type.
- Jakarta Persistence 3.1 now supports java.util.UUID, to be used as a basic type of field, which is very convenient for entity IDs in the cloud environment since many databases don’t automatically generate UUID. It also adds several new functions to the Query Language and Criteria API, making Jakarta Persistence much more versatile and allowing developers to write more complex queries utilizing the full power of entity mappings without having to resort to native SQL queries.
- Jakarta Faces 4.0 brings a new API to define the full view (HTML Pages) using only Java code.
- Jakarta Security 3.0 brings necessary and standard support for the OpenID Connect protocol, which has become widely used to login using other services, e.g., Facebook, Google, Twitter, etc.
- Jakarta Concurrency 3.0 adds asynchronous methods with a new Asynchronous annotation, which doesn’t require using EJB, and allows developers to specify the thread pool.
In addition to these, a significant number of other component specifications are introducing major or minor version updates to reflect significant changes in their respective specifications and APIs. Besides, many deprecated features have been removed, streamlining and enhancing the developer experience.
Regarding this release, Reza Rahman, principal program manager at Microsoft and Jakarta EE ambassador, discussing the Jakarta EE 10 release during the launch celebration, stated:
Jakarta EE 10 is an incredibly important release. The earlier releases, such as 9 and 9.1, were essential; however, they didn’t bring any direct value in terms of changes or innovations. This release is foundationally important as it brings the long pending set of changes that, if you are somebody who relies on Jakarta EE as a technology you haven’t really had in the past few years, that’s going to change. And hopefully, moving forward and, more importantly, it’s also sort of proof in the way that the Jakarta EE process can also continue to deliver features and innovations in the same way that Java EE had done for some period of time.
Alongside the release of Jakarta EE 10, the Eclipse Foundation also released the results of its 2022 Jakarta EE Developer Survey, which include the following key results:
- Jakarta EE usage increased from 47% in 2021 to 53% in 2022, while Spring/Spring Boot and MicroProfile usage experienced slight declines.
- The Jakarta EE community is looking for faster support from existing Java EE/Jakarta EE or cloud vendors (28%).
- Despite being released less than a year ago, the use of Java 17 (the LTS release of Java SE) has surged to 26%. Java 11 use remains steady at 57% (58% in 2021). This is a good indicator that enterprises closely follow the LTS releases.
Developers who wish to evaluate Jakarta EE 10 can leverage the article by Ivar Grimstad, Jakarta EE Developer Advocate, and his presentation at JavaZone 2022, read the specifications, and download the compatible products.
Java News Roundup: JDK 19 and Jakarta EE 10 Released, String Templates, Payara Platform
MMS • Michael Redlich
Article originally posted on InfoQ. Visit InfoQ
This week’s Java roundup for September 19th, 2022 features news from OpenJDK, JDK 19, JDK 20, Amazon Corretto 19, BellSoft Liberica JDK 19, Jakarta EE 10, multiple Spring Framework updates, Quarkus 2.12.3, Payara Platform updates, Micronaut 3.7.0, GraalVM Native Build Tools 0.9.14, JobRunr 5.2.0, PrimeFaces point releases, Failsafe 3.3.0, Apache Groovy 3.0.13 and Apache Log4j2 2.19.0.
OpenJDK
JEP 430, String Templates (Preview), was promoted from its JEP Draft 8273943 to Candidate status. This preview JEP, under the auspices of Project Amber, proposes to enhance the Java programming language with string templates, string literals containing embedded expressions, that are interpreted at runtime where the embedded expressions are evaluated and verified.
JDK 19
Oracle has released version 19 of the Java programming language and virtual machine this past week, which ships with a final feature set of seven JEPs. More details may be found in this InfoQ news story.
Amazon Corretto
Amazon has released Amazon Corretto 19, their downstream distribution of OpenJDK 19, that is available on Linux, Windows, and macOS. Developers may download this latest version from this site.
Liberica JDK
Similarly, BellSoft has released LibericaJDK 19, their downstream distribution of JDK 19. Developers may download this latest version from this site.
JDK 20
Build 16 of the JDK 20 early-access builds was also made available this past week, featuring updates from Build 15 that include fixes to various issues. Further details on this build may be found in the release notes.
For JDK 20, developers are encouraged to report bugs via the Java Bug Database.
Jakarta EE
The Jakarta EE Working Group has released Jakarta EE 10, the third major, and fourth overall, release since Oracle donated Java EE 8 to the Eclipse Foundation in 2017. This release provides new functionality in over 20 component specifications through version updates. Also new for Jakarta EE 10 is the Core profile that joins the existing Platform and Web profiles, all of which have compatible implementations. InfoQ will follow up with a more detailed news story.
Spring Framework
It was a very busy week for the Spring teams as they released point and milestone versions for a number of their projects along with publishing a common vulnerability and exposure (CVE).
The Spring Data REST team has published CVE-2022-31679, Potential Unintended Data Exposure for Resource Exposed by Spring Data REST, a vulnerability in which an attacker can craft HTTP requests that expose hidden entity attributes within applications that allow HTTP PATCH
access to resources exposed by Spring Data REST.
Versions 2.7.4 and 2.6.12 of Spring Boot were made available to the Java community. Both versions support JDK 19 and feature numerous bug fixes, improvements in documentation and dependency upgrades such as: Spring Framework 5.3.23, Hibernate 5.6.11.Final, Netty 4.1.82.Final, Rector 2020.0.23, Groovy 3.0.13, Dropwizard Metrics 4.2.12 and Postgresql 42.3.7. More details on each release may be found in the release notes for version 2.7.4 and version 2.6.12.
On the road to Spring Boot 3.0, the fifth milestone release was made available with notable new features such as: improved Ahead-of-Time processing and native image support; improved sanitation of actuator endpoints; and a reinstatement of support for Eclipse Jersey after fixing an issue with the common-core
module. Further details on this release may be found in the release notes.
Versions 2022.0.0-M6, 2021.2.3, and 2021.1.7 of Spring Data have been released that ship with bug fixes and dependency upgrades to the corresponding versions of Spring Data sub-projects such as: Spring Data REST, Spring Data JPA, Spring Data MongoDB, Spring Data for Apache Cassandra, Spring Data Neo4j and Spring Data KeyValue. These releases also include the fix to address the aforementioned CVE-2022-31679 vulnerability.
Versions 6.0.0-M7 and 5.8.0-M3 of Spring Security have been released. New features in version 6.0.0-M7 include: support for native-image in the @PreAuthorize
annotation; a performance enhancement in the HttpSessionRequestCache
class; and the removal of the FilterSecurityInterceptor
class, now deprecated, from the WebSecurity
class in favor of the AuthorizationFilter
class. New features for version 5.8.0-M3 include: new interfaces for CSRF request processing; AspectJ support to the @EnableMethodSecurity
annotation; and support for lazy reading of an implementation of the CsrfToken
interface by the LazyCsrfTokenRepository
class to complement the existing lazy saving of a token. It is worth noting that there are breaking changes for version 6.0.0-M7. More details on these releases may be found in the release notes for version 6.0.0-M7 and version 5.8.0-M3.
The second milestone release of Spring Cloud Dataflow 2.10.0 has been made available featuring dependency upgrades to Spring Boot 2.7.3, Spring Framework 5.3.22 and Spring Cloud 2021.0.3. Support for MySQL 5.7+, using the MariaDB JDBC driver, has been restored after it was briefly removed in Spring Cloud Dataflow 2.10.0-M1. Further details on this release may be found in the release notes.
Versions 5.0.0-M6 and 4.3.7 of Spring Batch have been released. Version 4.3.7 delivers bug fixes, improvements in documentation and dependency upgrades such as: Spring Framework 5.3.23; Spring Data 2.5.12; Spring Integration 5.5.15; and Spring Kafka 2.7.14. Version 5.0.0-M6 delivers new features such as: support for native-image in the AbstractJobRepositoryFactoryBean
class; support to configure the transaction manager in the SimpleJobOperator
and SimpleJobExplorer
classes; and revisit the configuration of infrastructure beans with the @EnableBatchProcessing
annotation. More details on these releases may be found in the release notes for version 5.0.0-M6 and version 4.3.7.
The second milestone release of Spring Authorization Server 1.0.0 merges enhancements from 0.4.x release train along with dependency upgrades to Spring Framework 6.0.0-M6, Spring Security 6.0.0-M7, mockito-core
4.8.0, jackson-bom
2.13.4 and nimbus-jose-jwt
9.24.4. Further details on this release may be found in the release notes.
The third milestone release of Spring Session 2022.0.0 has been made available that ships with updates to sub-projects: Spring Session Core 3.0.0-M4, Spring Session Data Redis 3.0.0-M4, Spring Session JDBC 3.0.0-M4, and Spring Session Hazelcast 3.0.0-M4.
Similarly, the second milestone release of Spring Authorization Server 0.4.0 ships with new features such as: the ability to add implementations of the AuthenticationProvider
and AuthenticationConverter
interfaces as an alternative to overriding default ones; and a check to verify that the client secret has not expired in ClientSecretAuthenticationProvider
class. More details may be found in the release notes.
Versions 6.0.0-M5 and 5.5.15 of Spring Integration have been made available. Version 5.5.15 features critical bug fixes and resolutions to deprecations of upstream dependencies. Notable changes in version 6.0.0-M5 include: support for Spring AOT, GraphQL and Apache Camel; the removal of the Remote Method Invocation (RMI) module in favor of more secure protocols; a new PostgresSubscribableChannel
class to rely on the native PostgreSQL push notifications; and a new ClientManager
interface to allow sharing the same MQTT client for different channel adapters. Developers are encouraged to read this migration guide for breaking changes and more details.
Spring for Apache Pulsar 0.1.0-M1, an experimental Spring project, has been released featuring numerous bug fixes and improvements. This version is based on JDK 17, Spring Boot 3.0.0-M5 and Spring Framework 6.0.0-M5. Further details on this release may be found in the release notes.
Spring for GraphQL 1.0.2 has been released that ships with new features such as: support for the @Arguments
annotation with Java’s Map
interface; support for path variables for redirect to a GraphiQL path; and new introspect controller methods on startup to determine if they need validation. More details on this release may be found in the release notes.
The first milestone release of Spring for GraphQL 1.1 was made available featuring support for JDK 17, Jakarta EE, and a Spring Framework 6.0 baseline. There was also an upgrade to GraphQL Java 19.x, the Java implementation of GraphQL, and new Micrometer Context Propagation library that replaces their internally developed context propagation mechanism.
Quarkus
Quarkus 2.12.3.Final has been released featuring: a dependency upgrade to Hibernate Search 6.1.7.Final; fixes for the request context leak in the Funqy Knative runtime and the MongoDB driver failing a DNS Lookup; and properly support generic bounds for implementations of the ParamConverterProvider
interface. Further details on this release may be found in the release notes.
Payara
Payara has released their September 2022 edition of the Payara Platform. Payara 6 Community Alpha 4 provides preview support for Jakarta EE 10 and includes 15 bug fixes, six component upgrades, three improvements and two security fixes. Payara is targeting a beta release for the Payara 6 Community edition to pass the Jakarta EE TCK. More details on this release may be found in the release notes.
Payara Enterprise 5.43.0 brings four bug fixes, a component upgrade to Eclipse Jersey 2.36, and an improvement to support an OpenID Connect token issuer field in Active Directory Federation Services (ADFS). Further details on this release may be found in the release notes.
Micronaut
The Micronaut Foundation has released Micronaut Framework 3.7.0 featuring improvements to numerous modules such as Micronaut for Spring, Micronaut Gradle Plugin, Micronaut GCP, Micronaut Test and Micronaut Reactor. This version also introduces two new modules, Micronaut CRaC and Micronaut Object Storage, to provide support for the Coordinated Restore at Checkpoint (CRaC) and a uniform API to create, read and delete objects within major cloud providers, respectively. More details on this release may be found in the release notes.
Oracle Labs
On the road to version 1.0, Oracle Labs has released version 0.9.14 of Native Build Tools, a GraalVM project consisting of plugins for interoperability with GraalVM Native Image. This latest release provides improvements such as: argument files are now stored in the build
directory of the Gradle Plugin and the target
directory of the Maven Plugin to address the workaround for an absolute path issue on Windows with older versions of GraalVM; and adding a native:compile
forking goal that can be initiated from the command line such as mvn native:compile
. Further details on this release may be found in the changelog.
Oracle Labs has also provided a community roadmap for features in upcoming GraalVM releases planned for October 2022 and January 2023 along with features planned beyond that timeframe.
JobRunr
Ronald Dehuysser, founder and primary developer of JobRunr, a utility to perform background processing in Java, has released version 5.2.0 that deliver improvements such as: the recurring jobs dashboard is now paged; and the query that returns counters for the dashboard and metrics uses 2-10 times less CPU cycles. More details on this release may be found In the release notes.
PrimeFaces
PrimeFaces, a provider of open-source UI component libraries, has provided point releases of versions 7.0.29, 8.0.21, 10.0.16 and 11.0.8. New features and enhancements include: a new source attribute to Confirm component; an upgrade to Moment.js 2.29.4 that addresses CVE-2022-31129, a vulnerability in which users who pass user-provided strings without sanity length checks to the moment()
constructor being vulnerable to regular expression denial of service (ReDoS) attacks; and adding an autoMonthFormat
attribute to the DatePicker
component.
Failsafe
Failsafe, a lightweight, zero-dependency library for handling failures in Java 8+, has released version 3.3.0 featuring API changes such as: the getStartTime()
method defined in the ExecutionContext
interface now returns an instance of type Instant
rather than an instance of type Duration
; and similarly, the getStartTime()
defined in ExecutionEvent
class now returns an instance of type Optional
rather than an instance of type Duration
. Also, the getFailure()
, getLastFailure()
, recordFailure()
and similar methods for recording exceptions, deprecated in a previous version, were removed in this release. Developers should use the getException()
, getLastException()
, recordException()
and similar methods. Further details on this release may be found in the changelog.
Apache Software Foundation
Apache Groovy 3.0.13 has been released featuring 44 bug fixes, improvements and a dependency upgrade to Spock 2.2. More details on this release may be found in the changelog.
Apache Log4j 2.19.0 has been released that ships with new features that add: support for SLF4J2 stack-valued MDC
class; and an implementation of the SLF4J2 fluent API.
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Evercore ISI analysts, led by Amit Daryanani, have reflected on the prospects of IBM (NYSE:IBM) potentially trying to replicate the Red Hat deal that proved to be a success despite a $34 billion price tag.
Daryanani reminded investors that IBM did over 25 M&A deals in the past 2 years, worth over $4 billion.
“We do not find this surprising as acquisitions are part of IBM’s medium-term financial model (mid-single-digit revenue growth at constant currency with M&A contributing 1-2 pts to growth),” Daryanani said in a client note.
However, IBM could still opt to do a large M&A deal to drive its top-line growth, as well as attempt to fundamentally transform its business. In this respect, the company could potentially dedicate as much as $30 billion for the right deal, although the management indicated this number could be closer to $20 billion.
“Higher growth tech companies have re-rated lower since the year began; with valuation multiples becoming more attractive vs. a year ago, we think it could make sense for IBM to look to M&A to as away to drive revenue acceleration and/or further transform their business. Given the success of the RHT acquisition, we think a potential large transformative deal could be viewed positively by investors,” the analyst added.
Evercore ISI’s screen of public market companies that could potentially be acquired by IBM resulted in about 80 results. For instance, companies like Zscaler (NASDAQ:ZS), Okta (NASDAQ:OKTA), DocuSign (NASDAQ:DOCU), RingCentral (NYSE:RNG), MongoDB (NASDAQ:MDB), and Gitlab (NASDAQ:GTLB), all found themselves on the list of potential M&A targets for IBM.
Article originally posted on mongodb google news. Visit mongodb google news
Android Studio Dolphin Extends Jetpack Compose, Wear OS, and Test Automation Integration
MMS • Sergio De Simone
Article originally posted on InfoQ. Visit InfoQ
The latest release of Android Studio, dubbed Dolphin, improves Jetpack Compose screen previews, extends Wear OS support, and introduces Gradle Managed Virtual Devices to simplify test automation.
Jetpack Compose screen preview gets three new features: multipreview annotations, an animation inspector, and recomposition counts. Multipreview annotations aim to reduce boilerplate code through preview definitions that specify which devices to generate previews for, the fonts and themes to use, and so on. Annotations can then be reused to avoid copy-pasting the definitions themselves, as developers had to do until now. The following snippet shows how you can define a FontScalePreviews
annotation and use it in a preview composable:
@Preview(
name = "small font",
group = "font scales",
fontScale = 0.5f
)
@Preview(
name = "large font",
group = "font scales",
fontScale = 1.5f
)
annotation class FontScalePreviews
...
@FontScalePreviews
@Composable
fun HelloWorldPreview() {
Text("Hello World")
}
The animation preview inspector helps previewing and fine-tuning animations by allowing you to freeze an animation or run it frame-by-frame.
The Compose recomposition count, available in the Layout Inspector, shows how often a view is recomposed, that is re-rendered. This can help identify cases where too frequent recomposition may negatively impact performance.
Gradle Managed Virtual Devices is a new feature that aims to make it easier to manage and setup emulators using for testing. Instead of having to manually execute all required steps to provision an emulator for testing, you can now describe which virtual devices you want in your build.gradle
file. The tool will then download the corresponding SDK, if necessary, provision and set up the emulator, and run your tests. This is how you can use this feature inside gradle.build
:
android {
managedDevices {
devices {
pixel2api30 (com.android.build.api.dsl.ManagedVirtualDevice) {
device = "Pixel 2"
apiLevel = 30
systemImageSource = "google-atd"
}
...
}
}
}
As mentioned, Wear OS support is also enhanced in Android Studio Dolphin. This includes a new Wear OS Emulator Pairing Assistant which helps managing and pairing multiple Wear OS devices; improved emulation toolbar which better aligns to physical devices and makes it possible to emulate palm gestures and tilting; and, better support for launching a Wear OS app into the exact state you expect it to be directly from the IDE.
As a final note, Android Studio Dolphin updates its compiler toolchain to IntelliJ 2021.3, which includes a number of improvements including better Kotlin debugging, improved suggestions, and remote coding support.
Android Studio Dolphin can be downloaded from Google Android website or installed directly from a previous version.
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MongoDB Inc. (NASDAQ:MDB) price closed lower on Friday, September 23, dropping -1.75% below its previous close.
A look at the daily price movement shows that the last close reads $198.20, with intraday deals fluctuated between $189.235 and $201.35. The company’s 5Y monthly beta was ticking 0.91. Taking into account the 52-week price action we note that the stock hit a 52-week high of $590.00 and 52-week low of $196.80. The stock subtracted -42.49% on its value in the past month.
MongoDB Inc., which has a market valuation of $13.62 billion, is expected to release its quarterly earnings report Mar 07, 2022 – Mar 11, 2022. Analysts tracking MDB have forecast the quarterly EPS to shrink by -0.28 per share this quarter, while the same analysts predict the annual EPS to hit -$0.21 for the year 2022 and up to $0.23 for 2024. In this case, analysts estimate an annual EPS growth of 64.40% for the year and 209.50% for the next year.
On average, analysts have forecast the company’s revenue for the quarter will hit $282.4 million, with the likely lows of $280.18 million and highs of $293.97 million. Staying with the analyst view, there is a consensus estimate of $1.19 billion for the company’s annual revenue in 2023. Per this projection, the revenue is forecast to grow 36.40% above that which the company brought in 2023.
Revisions to the company’s EPS highlights a short term direction of a stock’s price movement, which in the last 7 days came up with 1 upward and no downward reviews. On the technical perspective front, indicators give MDB a short term outlook of 100% Sell on average. Looking at the stock’s medium term indicators we note that it is averaging as a 50% Sell, while an average of long term indicators are currently assigning the stock as 100% Sell.
Here is a look at the average analyst rating for the stock as represented on a scale of 1.00 to 5.00, with the extremes of 1.00 and 5.00 suggesting the stock is strong buy or strong sell respectively. Specifically, 23 analysts have assigned MDB a recommendation rating as follows: 5 rate it as a Hold; 15 advise Buy while 2 analyst(s) assign an Overweight rating. 0 analyst(s) have tagged the MongoDB Inc. (MDB) stock as Underweight, with 1 recommending Sell. In general, analysts have rated the stock Overweight, a scenario likely to bolster investors out for an opportunity to add to their holdings of the company’s shares.
The overview shows that MDB’s price is at present -26.08% off the SMA20 and -35.52% from the SMA50. The Relative Strength Index (RSI) metric on the 14-day timeframe is pointing at 26.97, with weekly volatility standing at 5.55%. The indicator jumps to 6.20% when calculated based on the past 30 days. MongoDB Inc. (NASDAQ:MDB)’s beta value is holding at 1.08, while the average true range (ATR) indicator is currently reading 16.96. Considering analysts have assigned the stock a price target range of $300.00-$445.00 as the low and high respectively, we find the trailing 12-month average consensus price target to be $360.01. Based on this estimate, we see that current price is roughly -54.06% off the estimated low and -128.52% off the forecast high. Investors will no doubt be excited to see the share price fall to $355.00, which is the median consensus price, and at that level MDB would be -82.3% from current price.
Turning out attention to how the MongoDB Inc. stock has performed in comparison to its peers in the industry, here’s what we find: MDB’s stock is -1.75% on the day and -62.12% in the past 12 months, while Progress Software Corporation (PRGS) traded -2.14% in the last session and was positioned -8.94% down on its price 12 months ago. Another comparison is with Pixelworks Inc. (PXLW) whose stock price was down -0.61% in the last trading session, and has flourished -69.59% over the past year. Elsewhere in the market, the S&P 500 Index has stumbled -1.72% in last trading session, with the Dow Jones Industrial also saw a negative session on the day with -1.62%.
An analysis of the MongoDB Inc. (NASDAQ:MDB) stock in terms of its daily trading volume indicates that the 3-month average is 1.66 million. However, this figure increases on the past 10-day timeline to an average of 2.3 million.
Current records show that the company has 68.33M in outstanding shares. The insiders’ percentage holdings are 2.60% of outstanding shares while the percentage share held by institutions stands at 92.20%. The stats also highlight that short interest as of Jul 14, 2022, stood at 3.87 million shares, which puts the short ratio at the time at 2.34. From this we can glean that short interest is 5.69% of company’s current outstanding shares. Notably, we see that shares short in July fall slightly given the previous month’s figure stood at 4.34 million. But the -63.21% downside, the stock’s price has registered year-to-date as of last trading, will likely reignite investor interest given the prospect of it rallying even higher.
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IFM Investors Pty Ltd lifted its stake in shares of MongoDB, Inc. (NASDAQ:MDB – Get Rating) by 8.7% during the 2nd quarter, according to its most recent 13F filing with the Securities and Exchange Commission. The fund owned 10,802 shares of the company’s stock after purchasing an additional 865 shares during the quarter. IFM Investors Pty Ltd’s holdings in MongoDB were worth $2,803,000 as of its most recent filing with the Securities and Exchange Commission.
Several other hedge funds and other institutional investors also recently made changes to their positions in MDB. Norges Bank bought a new stake in shares of MongoDB during the 4th quarter valued at approximately $277,934,000. Jennison Associates LLC bought a new stake in MongoDB during the 1st quarter worth approximately $113,395,000. 1832 Asset Management L.P. grew its holdings in MongoDB by 19.3% during the 1st quarter. 1832 Asset Management L.P. now owns 1,028,400 shares of the company’s stock worth $450,095,000 after acquiring an additional 166,400 shares during the last quarter. Wellington Management Group LLP grew its holdings in MongoDB by 26.4% during the 1st quarter. Wellington Management Group LLP now owns 672,545 shares of the company’s stock worth $298,334,000 after acquiring an additional 140,260 shares during the last quarter. Finally, Vanguard Group Inc. grew its holdings in MongoDB by 2.1% during the 1st quarter. Vanguard Group Inc. now owns 5,970,224 shares of the company’s stock worth $2,648,332,000 after acquiring an additional 121,201 shares during the last quarter. 89.85% of the stock is owned by institutional investors.
Insider Activity at MongoDB
In other MongoDB news, Director Archana Agrawal sold 663 shares of the business’s stock in a transaction on Monday, August 29th. The shares were sold at an average price of $345.55, for a total transaction of $229,099.65. Following the completion of the sale, the director now owns 2,080 shares in the company, valued at approximately $718,744. The sale was disclosed in a document filed with the Securities & Exchange Commission, which is accessible through the SEC website. In other MongoDB news, Director Archana Agrawal sold 663 shares of the business’s stock in a transaction on Monday, August 29th. The shares were sold at an average price of $345.55, for a total transaction of $229,099.65. Following the completion of the sale, the director now owns 2,080 shares in the company, valued at approximately $718,744. The sale was disclosed in a document filed with the Securities & Exchange Commission, which is accessible through the SEC website. Also, insider Thomas Bull sold 489 shares of the business’s stock in a transaction on Tuesday, July 5th. The shares were sold at an average price of $264.45, for a total transaction of $129,316.05. Following the sale, the insider now owns 17,104 shares of the company’s stock, valued at approximately $4,523,152.80. The disclosure for this sale can be found here. Insiders have sold 69,789 shares of company stock worth $18,925,825 in the last quarter. Company insiders own 5.70% of the company’s stock.
MongoDB Stock Down 1.8 %
MongoDB stock opened at $194.73 on Monday. The company has a quick ratio of 4.02, a current ratio of 4.02 and a debt-to-equity ratio of 1.70. MongoDB, Inc. has a 12-month low of $189.24 and a 12-month high of $590.00. The firm’s fifty day moving average is $299.65 and its 200 day moving average is $314.70. The company has a market capitalization of $13.38 billion, a PE ratio of -36.33 and a beta of 0.95.
MongoDB (NASDAQ:MDB – Get Rating) last released its earnings results on Wednesday, August 31st. The company reported ($1.69) earnings per share (EPS) for the quarter, missing analysts’ consensus estimates of ($1.52) by ($0.17). MongoDB had a negative net margin of 33.43% and a negative return on equity of 52.05%. The company had revenue of $303.66 million for the quarter, compared to analyst estimates of $282.31 million. During the same quarter in the previous year, the firm earned ($1.15) EPS. The firm’s revenue was up 52.8% on a year-over-year basis. As a group, sell-side analysts predict that MongoDB, Inc. will post -5.36 EPS for the current fiscal year.
Wall Street Analysts Forecast Growth
MDB has been the topic of a number of research reports. Robert W. Baird reduced their target price on shares of MongoDB from $360.00 to $330.00 and set an “outperform” rating on the stock in a report on Thursday, September 1st. The Goldman Sachs Group reduced their target price on shares of MongoDB to $430.00 in a report on Tuesday, September 6th. Barclays reduced their target price on shares of MongoDB from $438.00 to $360.00 and set an “overweight” rating on the stock in a report on Thursday, September 1st. Canaccord Genuity Group boosted their target price on shares of MongoDB from $300.00 to $360.00 and gave the stock a “buy” rating in a report on Thursday, September 1st. Finally, Needham & Company LLC dropped their price target on shares of MongoDB from $350.00 to $330.00 and set a “buy” rating on the stock in a research report on Thursday, September 1st. One investment analyst has rated the stock with a sell rating and eighteen have issued a buy rating to the company. According to MarketBeat, the company currently has an average rating of “Moderate Buy” and a consensus price target of $386.83.
MongoDB Company Profile
MongoDB, Inc provides general purpose database platform worldwide. The company offers MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premise, or in a hybrid environment; MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; and Community Server, a free-to-download version of its database, which includes the functionality that developers need to get started with MongoDB.
Further Reading
- Get a free copy of the StockNews.com research report on MongoDB (MDB)
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Want to see what other hedge funds are holding MDB? Visit HoldingsChannel.com to get the latest 13F filings and insider trades for MongoDB, Inc. (NASDAQ:MDB – Get Rating).
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MongoDB, Inc. (NASDAQ:MDB – Get Rating) has been assigned an average recommendation of “Moderate Buy” from the nineteen research firms that are covering the company, Marketbeat.com reports. One investment analyst has rated the stock with a sell rating and seventeen have assigned a buy rating to the company. The average 12 month price target among analysts that have issued ratings on the stock in the last year is $386.83.
MDB has been the subject of several analyst reports. Canaccord Genuity Group increased their target price on shares of MongoDB from $300.00 to $360.00 and gave the company a “buy” rating in a report on Thursday, September 1st. Oppenheimer decreased their price objective on shares of MongoDB from $490.00 to $400.00 and set an “outperform” rating for the company in a report on Thursday, June 2nd. Piper Sandler decreased their price objective on shares of MongoDB from $375.00 to $350.00 and set an “overweight” rating for the company in a report on Thursday, September 1st. Barclays decreased their price objective on shares of MongoDB from $438.00 to $360.00 and set an “overweight” rating for the company in a report on Thursday, September 1st. Finally, Citigroup cut their target price on shares of MongoDB from $450.00 to $445.00 and set a “buy” rating for the company in a research report on Thursday, September 1st.
Insiders Place Their Bets
In related news, CEO Dev Ittycheria sold 16,991 shares of MongoDB stock in a transaction on Friday, September 9th. The shares were sold at an average price of $250.66, for a total value of $4,258,964.06. Following the transaction, the chief executive officer now directly owns 199,753 shares of the company’s stock, valued at $50,070,086.98. The sale was disclosed in a legal filing with the SEC, which can be accessed through this link. In related news, CEO Dev Ittycheria sold 16,991 shares of MongoDB stock in a transaction on Friday, September 9th. The shares were sold at an average price of $250.66, for a total value of $4,258,964.06. Following the transaction, the chief executive officer now directly owns 199,753 shares of the company’s stock, valued at $50,070,086.98. The sale was disclosed in a legal filing with the SEC, which can be accessed through this link. Also, Director Dwight A. Merriman sold 629 shares of MongoDB stock in a transaction on Tuesday, June 28th. The stock was sold at an average price of $292.64, for a total transaction of $184,070.56. Following the completion of the transaction, the director now directly owns 1,322,755 shares in the company, valued at $387,091,023.20. The disclosure for this sale can be found here. Over the last ninety days, insiders have sold 69,789 shares of company stock valued at $18,925,825. 5.70% of the stock is currently owned by corporate insiders.
Institutional Trading of MongoDB
Large investors have recently added to or reduced their stakes in the stock. Royal London Asset Management Ltd. boosted its holdings in shares of MongoDB by 4.8% during the 2nd quarter. Royal London Asset Management Ltd. now owns 23,722 shares of the company’s stock valued at $6,158,000 after buying an additional 1,078 shares in the last quarter. Legal & General Group Plc boosted its holdings in shares of MongoDB by 8.0% during the 2nd quarter. Legal & General Group Plc now owns 395,501 shares of the company’s stock valued at $102,633,000 after buying an additional 29,421 shares in the last quarter. ExodusPoint Capital Management LP bought a new stake in shares of MongoDB during the 2nd quarter valued at $17,081,000. IMA Wealth Inc. bought a new stake in shares of MongoDB during the 2nd quarter valued at $675,000. Finally, Infini Capital Management Ltd bought a new stake in shares of MongoDB during the 2nd quarter valued at $441,000. Institutional investors own 89.85% of the company’s stock.
MongoDB Stock Performance
MDB opened at $194.73 on Friday. The company has a current ratio of 4.02, a quick ratio of 4.02 and a debt-to-equity ratio of 1.70. The company’s fifty day moving average price is $299.65 and its two-hundred day moving average price is $314.70. MongoDB has a 1-year low of $189.24 and a 1-year high of $590.00. The company has a market cap of $13.38 billion, a price-to-earnings ratio of -36.33 and a beta of 0.95.
MongoDB (NASDAQ:MDB – Get Rating) last released its quarterly earnings data on Wednesday, August 31st. The company reported ($1.69) earnings per share for the quarter, missing the consensus estimate of ($1.52) by ($0.17). MongoDB had a negative return on equity of 52.05% and a negative net margin of 33.43%. The business had revenue of $303.66 million for the quarter, compared to analyst estimates of $282.31 million. During the same quarter in the previous year, the company posted ($1.15) EPS. The business’s quarterly revenue was up 52.8% on a year-over-year basis. On average, analysts expect that MongoDB will post -5.36 EPS for the current fiscal year.
MongoDB Company Profile
MongoDB, Inc provides general purpose database platform worldwide. The company offers MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premise, or in a hybrid environment; MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; and Community Server, a free-to-download version of its database, which includes the functionality that developers need to get started with MongoDB.
Further Reading
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Organizations and businesses must use a range of measures, protocols, and tools to protect their databases from cybercriminals. If breached, malicious actors can gain access to sensitive information that they can use for financial gain. Security teams must adapt and constantly improve to protect against ever-evolving security threats, and maintain the integrity of a database.
This article will discuss the major database security threats, and how you can prevent them.
1. SQL Injection Attacks
SQL injection is the most common threat. This attack is performed by entering a query into a SQL form, and if the database interprets the result as “true” it enables access to the database. These attacks usually target relational database management systems (RDBMS) based on the SQL programming language.
Databases not based on SQL (NoSQL) are not susceptible to such attacks. Instead, NoSQL databases are targeted by queries delivered by an end-user that uses commands to execute malware.
Both methods are equally threatening, getting around verification systems by obtaining credentials and then exposing the structure and content of the database. A successful attack would give an attacker free reign of everything contained within the database.
2. Malware
Malware is designed to target vulnerabilities on a network, granting access to a database, or causing damage to it. These vulnerabilities relate to unprotected endpoints on a network that can be exploited via a range of different attacks.
For IT teams to protect against malware attacks, it is important to identify the attack surface of a network. The attack surface refers to the number of vulnerabilities on a network that a cybercriminal could target.
3. Denial of Service (DoS/DDoS) Attacks
A Denial of Service (DoS) attack occurs when a database server receives more requests than it can process, causing the system to become unstable or crash. These erroneous requests can be created by an attacker and directed at a specific target. The volume of fake requests overwhelms the system, resulting in downtime for the victim.
A Distributed Denial of Service (DDoS) attack uses a botnet (a very large network of computers) to create a huge amount of traffic that even the most advanced security systems would struggle to prevent. The best defense against these types of attacks is to employ a cloud-based DoS protection service that can help to limit high and suspicious traffic volume.
4. Poor Permission Management
Many organizations fail to change the default security settings from when a database server is initially installed. Just a few years ago, as many as 20% of companies were not even changing default passwords on privileged accounts. This leaves them vulnerable to an attack from attackers who know the defaults and, more importantly, how they can be exploited.
Criminals may obtain log-in details of privileged accounts when accessing the database. Inactive accounts can also present a risk if an attacker is aware of their existence. This is why permissions management should be at the forefront when developing the cybersecurity portion for your business as a whole, using zero trust protocols to prevent unauthorized access.
Occasionally, a user can be accidentally given permissions to the database that they shouldn’t have access to. This presents an opportunity for hackers to target such users with phishing scams or other tactics that attempt to launch malware on their devices.
Cybercriminals can also attempt to seize control of the organization’s data management system, altering privileges so they can gain database access at any time.
5. Database Backup Exposures
Backing up a database regularly is obviously recommended, but often, many of these backups are left unprotected, making them a common target for attackers. Securing backups is especially vital for industries that hold vital customer information, such as healthcare providers or banks and financial institutions.
To prevent database exposures, you should:
- Encrypt your database and any backups that are made.
- Conduct regular audits of databases and their backups to record who has been accessing this data.
6. Inadequate Auditing
Poor auditing can present a golden opportunity to cybercriminals, rendering your database non-compliant with data security regulations. Organizations are required to register all events that take place on a database server and conduct regular auditing. Of course, such auditing is best using automated systems.
A failure to implement effective auditing procedures increases the chances of a successful cyberattack. However, it is also important that any automated auditing software does not impact the overall performance of the database.
7. Unprotected Databases Due to Misconfiguration
Attacks resulting from misconfiguration are also commonly caused because of unprotected databases when some parameters and accounts are left unchanged from their initial default settings. Using these defaults, an experienced attacker can gain access. This is why businesses should always ensure their databases are being managed correctly, using thorough procedures and audits. Database management should be conducted by an expert, whether this is an in-house professional or an external cybersecurity firm.
8. Credentials
Social engineering attacks, such as phishing or click-bait advertising can be used to obtain log-in credentials that an attacker can use to access a network and database.
9. Unencrypted data
Data encryption is a fundamental and crucial component of any cybersecurity policy, and especially when it comes to the protection of financial information. All account and financial data that is stored within your financial institution should be encrypted. This way, even if any of the data is stolen, encryption guarantees that it is unusable. In fact, at least one cybersecurity law prescribes data encryption for compliance with the regulation
How To Prevent Database Security Threats
Below are preventative measures to reduce your database’s vulnerability regarding cybersecurity threats:
- Better employee training so best practices are used daily.
- Determining the attack surface of your network and database.
- Using a zero trust system.
- Deleting inactive accounts and limiting privileges for standard users.
- Encrypting the database and all backups.
- Blocking potentially malicious web requests.
- Monitoring who accesses the database and analyzing usage patterns.
- Using masking to hide database fields that contain sensitive information.
Conclusion
There are many different security threats that can pose a significant risk to the data of your organization and clients. The most common database threat is SQL injection, but attacks such as Denial of Service and malware are equally dangerous. Training your employees, using encryption, and managing user privileges are some of the best ways to protect your database from a cyberattack.
About the Author:
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Article originally posted on Database Journal – Daily Database Management & Administration News and Tutorials. Visit Database Journal – Daily Database Management & Administration News and Tutorials
Structured Query Language – also known as SQL – is one of the most widely used programming languages in the world. Without a doubt, it is the most widely used language for querying relational database management systems (RDBMS) around the globe. As languages go, SQL is fairly straightforward to learn, with concise and clear-cut syntax and straightforward logic elements. As the de facto standard language for database queries, there is no shortage of learning resources for database programmers and database administrators to learn SQL. In this tutorial, we list the top online courses to learn SQL.
Online Courses to Learn SQL
Structure Query Language comes in many flavors – from straight SQL to derivatives like MySQL, Transactional SQL (also known as T-SQL), and PostgreSQL – to name but a few. These different flavors have their own rules and syntax and work with different database systems. Because of that, the courses listed in this database tutorial cover not just vanilla SQL, but MySQL, PostgreSQL, T-SQL, and MS SQL. The online courses are for database admins, database developers, and web developers who create database-driven web apps, and anyone who needs to programmatically (or manually) query relational tables.
MySQL and SQL for Beginners from TechRepublic Academy
The MySQL and SQL for Beginners database administration course from TechRepublic Academy starts off our list because it tackles two of the most powerful database technologies: the SQL language and the ever-popular MySQL database system. The course is 18 hours long and features 136 separate lectures, taught by expert software developer, John Purcell.
Students will learn basic SQL syntax and commands, including how to query, update, and manipulate information in MySQL databases. They will further learn how to configure and setup a MySQL relational database, including how to secure a database and create users. Additional database management principles like transactions, database isolation, triggers, views, and stored procedures will also be discussed.
Another great thing about this course is that it sets would-be database administrators and database programmers up to learn other relational database models and platforms, like advanced SQL, Oracle, and more. Further, it comes with a certificate of completion, which is a nice addition to your resume and LinkedIn profile.
You can learn more about this online MySQL and SQL course by visiting its TechRepublic Academy page: MySQL and SQL for Beginners.
Database Administration Super Bundle from TechRepublic Academy
The Database Administration Super Bundle is not simply a single online course, but, instead, a bundle of 9 separate – though interweaved – courses covering a plethora of SQL and database management topics through 468 individual lessons. It takes an estimated 85 hours to complete the bundle, which may sound daunting at first, but keep in mind that the courses are on-demand and you can take them at your leisure and whatever pacing you desire.
The bundle begins by showcasing NoSQL and how to use it to model data, build complicated and powerful web applications, and work with the MongoDB database system. NoSQL design, data aggregation, syntax, and general concepts will be taught. How to use Node.js and MongoDB, including installation and configuration, are also part of the course.
Course number two covers working with MySQL databases to create web applications. Basic database administration techniques and database structure are talked about. A walkthrough of MySQL tools is also included. From there, the bundle returns to MongoDB and the theory of constructing dynamic web apps. GridFS and the PHP and Python programming languages are also included. Database concepts like optimization, replication, and sharding are explored as well.
Part four of the database course bundle takes an 18 hour deep dive into enterprise data integration and data analytics with Informatica. Great detail about the usage and functions of Informatica is uncovered, as well as database architecture, ETL tools, database design, and workflows.
Part five is all about data visualization, using the powerful database tool Tableau. From there, part six curtails into Microsoft SQL Server administration. Part seven builds even further upon this branch of database administration, as students go from MS SQL novices to MS SQL “ninjas” and advanced users.
Finally, the last two courses in this bundle cover advanced database programming and administration topics including predictive modeling, regression models, database analytics, and database project management principles, including Six Sigma, lean, and other project management methodologies.
You can learn more or sign up for this online database course by visiting its listing on TechRepublic Academy: Database Administration Super Bundle.
The Microsoft SQL Server and T-SQL Course for Beginners
If you are looking to work in an organization that works in a Microsoft-related environment, the Microsoft SQL Server and T-SQL Course for Beginners might be right up your alley. The course is a gentle introduction to SQL and Microsoft SQL Server, weighing in at a light four hours for completion. It starts with an overview of common misconceptions about databases and the SQL language and then moves on to setting up SQL Server and SSMS. From there, pupils learn how data is stored in MS SQL and go over a variety of different, practical, and real-world SQL scenarios you might encounter.
Students taking this MS SQL online course will also learn Data Definition Language (DDL) commands, Data Manipulation Language (DML) commands, and Data Control Language (DCL) commands – all of which are used to manipulate data and table structures in RDBMS.
To learn more about this online database management course, visit its listing page on TechRepublic Academy: The Microsoft SQL Server and T-SQL Course for Beginners.