Month: June 2023

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New Jersey, N.J. – A2Z Market Research announces the release of Database as a Service Platform Market research report. The market is predicted to grow at a healthy pace in the coming years. Database as a Service Platform Market 2023 research report presents an analysis of market size, share, and growth, trends, cost structure, and statistical and comprehensive data of the global market.

A Database-as-a-Service (DBaaS) platform is a cloud-based offering that provides users with a fully-managed, hosted database solution. It offers both on-demand scalability and operational agility to ensure businesses can quickly and easily access the storage and computing resources they need. The DBaaS platform provides users with an easy-to-deploy database, as well as automated backup and recovery, automatic failover, and support for various database management systems (DBMS) such as MySQL, PostgreSQL, and MongoDB.

Get the PDF Sample Copy (Including FULL TOC, Graphs, and Tables) of this report @:

https://a2zmarketresearch.com/sample-request/1086219

Some of the Top companies influencing this Market include:

AWS,  Caspio,  DataStax,  Fusioo,  Google,  IBM,  Kintone,  Microsoft,  MongoDB,  Ninox,  Oracle,  SAP,  Zoho Corporation

The report, with the help of quick and dirty business profiles, project reasonableness investigation, SWOT assessment, and one or two experiences about the key associations working in the Database as a Service Platform Market, shows a point-by-point logical record of the market’s cutthroat situation. The report moreover shows a survey of the impact of late advancements on the markets future improvement possibilities.

Market Segmentation: By Type

Private Cloud

Public Cloud

Hybrid Cloud

Market Segmentation: By Application

Large Enterprises

SMEs

For Any Query or Customization, Inquire @:

 https://a2zmarketresearch.com/ask-for-customization/1086219

Geographic analysis

The global Database as a Service Platform market has been spread across North America, Europe, Asia-Pacific, the Middle East and Africa, and the rest of the world.

COVID-19 Impact Analysis

The pandemic of COVID-19 has emerged in lockdown across regions, line limitations, and breakdown of transportation organizations. Furthermore, the financial vulnerability Database as a Service Platform Market is a lot higher than in past flare-ups like the extreme intense respiratory condition (SARS), avian influenza, pig influenza, bird influenza, and Ebola, inferable from the rising number of contaminated individuals and the vulnerability about the finish of the crisis. With the rapid rising cases, the worldwide Database as a Service Platform refreshments market is getting influenced from multiple points of view.

Table of Contents

Global Database as a Service Platform Market Research Report 2023 – 2029

Chapter 1 Database as a Service Platform Market Overview

Chapter 2 Global Economic Impact on Industry

Chapter 3 Global Market Competition by Manufacturers

Chapter 4 Global Production, Revenue (Value) by Region

Chapter 5 Global Supply (Production), Consumption, Export, Import by Regions

Chapter 6 Global Production, Revenue (Value), Price Trend by Type

Chapter 7 Global Market Analysis by Application

Chapter 8 Manufacturing Cost Analysis

Chapter 9 Industrial Chain, Sourcing Strategy and Downstream Buyers

Chapter 10 Marketing Strategy Analysis, Distributors/Traders

Chapter 11 Market Effect Factors Analysis

Chapter 12 Global Database as a Service Platform Market Forecast

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Contact Us:

Roger Smith

1887 WHITNEY MESA DR HENDERSON, NV 89014

[email protected]

+1 775 237 4157

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Gulf International Bank UK Ltd cut its holdings in shares of MongoDB, Inc. (NASDAQ:MDB – Get Rating) by 25.4% in the first quarter, according to its most recent disclosure with the Securities and Exchange Commission (SEC). The firm owned 9,066 shares of the company’s stock after selling 3,081 shares during the period. Gulf International Bank UK Ltd’s holdings in MongoDB were worth $2,113,000 as of its most recent filing with the Securities and Exchange Commission (SEC).

Other institutional investors and hedge funds also recently added to or reduced their stakes in the company. Skandinaviska Enskilda Banken AB publ raised its position in shares of MongoDB by 2.5% in the fourth quarter. Skandinaviska Enskilda Banken AB publ now owns 11,467 shares of the company’s stock worth $2,256,000 after acquiring an additional 277 shares during the period. Lindbrook Capital LLC raised its position in shares of MongoDB by 350.0% in the fourth quarter. Lindbrook Capital LLC now owns 171 shares of the company’s stock worth $34,000 after acquiring an additional 133 shares during the period. Principal Financial Group Inc. raised its position in shares of MongoDB by 12.3% in the fourth quarter. Principal Financial Group Inc. now owns 8,452 shares of the company’s stock worth $1,664,000 after acquiring an additional 924 shares during the period. DekaBank Deutsche Girozentrale raised its position in shares of MongoDB by 30.6% in the fourth quarter. DekaBank Deutsche Girozentrale now owns 11,063 shares of the company’s stock worth $2,179,000 after acquiring an additional 2,591 shares during the period. Finally, Los Angeles Capital Management LLC raised its position in shares of MongoDB by 257.8% in the fourth quarter. Los Angeles Capital Management LLC now owns 14,085 shares of the company’s stock worth $2,772,000 after acquiring an additional 10,148 shares during the period. 89.22% of the stock is currently owned by institutional investors and hedge funds.

MongoDB Stock Performance

MongoDB stock opened at $389.99 on Friday. The firm has a 50 day simple moving average of $295.63 and a 200-day simple moving average of $238.81. MongoDB, Inc. has a 1-year low of $135.15 and a 1-year high of $398.89. The company has a debt-to-equity ratio of 1.44, a current ratio of 4.19 and a quick ratio of 4.19. The stock has a market cap of $27.31 billion, a price-to-earnings ratio of -83.51 and a beta of 1.04.

MongoDB (NASDAQ:MDB – Get Rating) last posted its quarterly earnings results on Thursday, June 1st. The company reported $0.56 earnings per share for the quarter, beating the consensus estimate of $0.18 by $0.38. MongoDB had a negative net margin of 23.58% and a negative return on equity of 43.25%. The business had revenue of $368.28 million during the quarter, compared to analysts’ expectations of $347.77 million. During the same quarter in the prior year, the company posted ($1.15) EPS. The business’s revenue for the quarter was up 29.0% on a year-over-year basis. On average, analysts expect that MongoDB, Inc. will post -2.85 EPS for the current year.

Analyst Upgrades and Downgrades

MDB has been the subject of a number of analyst reports. Wedbush decreased their price objective on shares of MongoDB from $240.00 to $230.00 in a research report on Thursday, March 9th. Needham & Company LLC upped their price objective on shares of MongoDB from $250.00 to $430.00 in a research report on Friday, June 2nd. Royal Bank of Canada upped their price target on shares of MongoDB from $400.00 to $445.00 in a research report on Friday. The Goldman Sachs Group upped their price target on shares of MongoDB from $420.00 to $440.00 in a research report on Friday. Finally, KeyCorp upped their price target on shares of MongoDB from $229.00 to $264.00 and gave the stock an “overweight” rating in a research report on Thursday, April 20th. One research analyst has rated the stock with a sell rating, two have issued a hold rating and twenty-one have given a buy rating to the stock. According to data from MarketBeat, the company currently has a consensus rating of “Moderate Buy” and a consensus price target of $349.87.

Insider Activity

In related news, CAO Thomas Bull sold 605 shares of the stock in a transaction that occurred on Monday, April 3rd. The shares were sold at an average price of $228.34, for a total transaction of $138,145.70. Following the completion of the transaction, the chief accounting officer now owns 17,706 shares of the company’s stock, valued at approximately $4,042,988.04. The transaction was disclosed in a filing with the Securities & Exchange Commission, which is accessible through the SEC website. In related news, CRO Cedric Pech sold 720 shares of the stock in a transaction that occurred on Monday, April 3rd. The shares were sold at an average price of $228.33, for a total transaction of $164,397.60. Following the completion of the transaction, the executive now owns 53,050 shares of the company’s stock, valued at approximately $12,112,906.50. The transaction was disclosed in a filing with the Securities & Exchange Commission, which is accessible through the SEC website. Also, CAO Thomas Bull sold 605 shares of the stock in a transaction that occurred on Monday, April 3rd. The stock was sold at an average price of $228.34, for a total transaction of $138,145.70. Following the transaction, the chief accounting officer now directly owns 17,706 shares of the company’s stock, valued at approximately $4,042,988.04. The disclosure for this sale can be found here. Insiders sold a total of 108,856 shares of company stock valued at $27,327,511 in the last 90 days. Company insiders own 4.80% of the company’s stock.

MongoDB Company Profile

(Get Rating)

MongoDB, Inc provides general purpose database platform worldwide. The company offers MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premise, or in a hybrid environment; and Community Server, a free-to-download version of its database, which includes the functionality that developers need to get started with MongoDB.

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This instant news alert was generated by narrative science technology and financial data from MarketBeat in order to provide readers with the fastest and most accurate reporting. This story was reviewed by MarketBeat’s editorial team prior to publication. Please send any questions or comments about this story to contact@marketbeat.com.

Before you consider MongoDB, you’ll want to hear this.

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While MongoDB currently has a “Moderate Buy” rating among analysts, top-rated analysts believe these five stocks are better buys.

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Investing.com — Here is your weekly Pro Recap on the biggest headlines out of tech this week: Tesla is slashed again after record rally, but picks up more momentum for its Supercharger network; FTC sues Amazon for allegedly deceptive consumer-facing practices; PayPal scores big loan deal with KKR; and MongoDB is riding high after solid investor day.

InvestingPro subscribers get tech headlines like these in real time. Never miss another market-moving alert.

Tesla’s Superchargers solidify dominance, even as shares are downgraded again

Rivian (NASDAQ:RIVN) said on Tuesday that it will adopt Tesla’s (NASDAQ:TSLA) charging standard, meaning owners of its electric vehicles will gain access to the already-dominant Supercharger network.

That access should open up as early as spring of next year, and Rivian also said it will standardize a Tesla-style charging port on its EVs as of 2025.

The announcement looks to add momentum to Tesla’s push to make Superchargers the standard for EVs in the U.S. and Canada following other recent agreements with General Motors (NYSE:GM) and Ford (NYSE:F).

Still, later in the week Morgan Stanley downgraded Tesla shares to Equal Weight from Overweight after their massive recent rally pushed Tesla’s valuation to what the firm considers “fair” levels.

The analyst has been a vocal Tesla bull in recent years, but is now stepping to the sidelines, saying in a note to clients:

I have to be up-front with you all. While the team has defended the Tesla [Overweight] rating all year, I did not see this 111% YTD rally coming (the S&P 500 is up 14% YTD, for context). We think it’s understandable and are sympathetic to the changes in the market narrative around the name.

With the downgrade call mostly based on the valuation, the firm added that Tesla remains “a ‘must own’ company in any EV portfolio,” emphasizing that it also benefits from the ongoing AI frenzy on Wall Street. It added:

We see continued evidence that Tesla is emerging as an industrial ‘standard bearer’ for one of the greatest industrial changes we’ve witnessed in over a century – the electric transport and renewable energy economy.

The analyst also raised the price target to $250 per share from the prior $200, with the new target suggesting a modest downside to Tesla’s Friday close of $256.60 – down 3% for the week. This is the third downgrade for Tesla stock this month after Barclays and CFRA analysts also lowered the shares to neutral ratings.

FTC sues Amazon for violating consumer protection laws

The Federal Trade Commission on Wednesday sued Amazon (NASDAQ: NASDAQ:AMZN) in Washington state federal court for violating consumer protection laws. The lawsuit alleges Amazon’s website knowingly “duped” millions of consumers into enrolling in Prime and then made it difficult for them to cancel.

Prime is Amazon’s paid subscription service that includes faster delivery and access to video streaming, songs and other features. The service costs $139 per year.

Amazon used manipulative, coercive, or deceptive user-interface designs known as “dark patterns” to trick consumers into enrolling in automatically renewing Prime subscriptions, the FTC said. It then knowingly complicated the cancellation process for Prime subscribers who sought to end their membership.

“Amazon tricked and trapped people into recurring subscriptions without their consent, not only frustrating users but also costing them significant money,” said FTC Chair Lina M. Khan. “These manipulative tactics harm consumers and law-abiding businesses alike. The FTC will continue to vigorously protect Americans from ‘dark patterns’ and other unfair or deceptive practices in digital markets.”

BofA reiterated a Buy rating on Amazon as they believe the lawsuit was expected, adding that Amazon’s stock reaction to the announcement shows the Street isn’t too worried. They noted:

In our view, the lawsuit potentially signals that the FTC does not have something potentially more impactful to pursue, such as pricing policies, 3P fees or 1P product competition.

Shares were up 1.25% for the week.

PayPal climbs on $3.3B loan deal with KKR

Shares of PayPal (NASDAQ:PYPL) climbed Tuesday after it announced a pact to sell $3.3 billion of buy now, pay later (BNPL) loans in Europe to private equity firm KKR (NYSE:KKR). KKR also agreed to purchase future loans, with a total deal value of about $43.6B.

BNPL is an increasingly popular method of payment that allows customers to pay the cost of a purchase over time.

“Our collaboration with KKR will allow us to accelerate our PayPal Pay Later originations alongside market demand in Europe while preserving free cash flow for other strategic initiatives,” said PayPal’s acting CFO Gabrielle Rabinovitch.

PayPal will allocate approximately $1B to incremental share repurchases in 2023 after the deal closes, increasing the total amount from $4B to $5B.

Keefe, Bruyette & Woods said the news should be “a headline positive.”

Shares of PayPal climbed 3% following the announcement, and are up 1.5% for the week. Year to date, the stock is down some 10%, lagging broader markets.

Analysts boost MongoDB targets after positive Investor Day

Wall Street analysts have weighed in positively on MongoDB’s (NASDAQ:MDB) investor event that took place Thursday in New York.

Analysts at Mizuho and Stifel, among others, hiked the price target on the stock after the company unexpectedly announced a new Stream Processing offering.

“We view this as an intriguing new opportunity for the co., although it is clearly very early and remains to be seen whether MDB can meaningfully broaden its value proposition beyond databases,” wrote Mizuho, which hiked the price target to $240 per share on the Neutral-rated stock.

Stifel is more bullish, reiterating a Buy rating on the stock and raising the target to $420 per share.

“New announcements were very well-received by the customers and partners we spoke with during the day. Overall, with the pace of new product introductions accelerating Mongo continues to solidify its leadership position among developer data platforms,” it said in a client note.

MongoDB shares closed over 4% higher Thursday, and were up fractionally for the week.

Senad Karaahmetovic contributed to this report.

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Shares of MongoDB, Inc. (NASDAQ:MDB – Get Rating) have earned an average rating of “Moderate Buy” from the twenty-four research firms that are covering the company, MarketBeat Ratings reports. One analyst has rated the stock with a sell rating, two have given a hold rating and twenty-one have given a buy rating to the company. The average 12-month target price among analysts that have issued a report on the stock in the last year is $349.87.

Several research firms have recently weighed in on MDB. Robert W. Baird lifted their target price on MongoDB from $390.00 to $430.00 in a research report on Friday. Wedbush decreased their price objective on MongoDB from $240.00 to $230.00 in a report on Thursday, March 9th. Barclays lifted their price objective on MongoDB from $280.00 to $374.00 in a report on Friday, June 2nd. Oppenheimer lifted their price objective on MongoDB from $270.00 to $430.00 in a report on Friday, June 2nd. Finally, Sanford C. Bernstein lifted their price objective on MongoDB from $257.00 to $424.00 in a report on Monday, June 5th.

Insider Buying and Selling

In other MongoDB news, CRO Cedric Pech sold 720 shares of the company’s stock in a transaction on Monday, April 3rd. The stock was sold at an average price of $228.33, for a total value of $164,397.60. Following the completion of the sale, the executive now directly owns 53,050 shares in the company, valued at approximately $12,112,906.50. The sale was disclosed in a document filed with the SEC, which can be accessed through this link. In related news, CRO Cedric Pech sold 720 shares of the stock in a transaction dated Monday, April 3rd. The stock was sold at an average price of $228.33, for a total transaction of $164,397.60. Following the transaction, the executive now owns 53,050 shares of the company’s stock, valued at approximately $12,112,906.50. The transaction was disclosed in a filing with the SEC, which is available through this hyperlink. Also, CAO Thomas Bull sold 605 shares of the stock in a transaction dated Monday, April 3rd. The stock was sold at an average price of $228.34, for a total value of $138,145.70. Following the transaction, the chief accounting officer now directly owns 17,706 shares in the company, valued at approximately $4,042,988.04. The disclosure for this sale can be found here. Over the last ninety days, insiders sold 108,856 shares of company stock worth $27,327,511. 4.80% of the stock is owned by corporate insiders.

Institutional Inflows and Outflows

Several institutional investors have recently added to or reduced their stakes in MDB. 1832 Asset Management L.P. increased its holdings in shares of MongoDB by 3,283,771.0% in the fourth quarter. 1832 Asset Management L.P. now owns 1,018,000 shares of the company’s stock valued at $200,383,000 after purchasing an additional 1,017,969 shares during the period. Price T Rowe Associates Inc. MD lifted its position in shares of MongoDB by 13.4% in the first quarter. Price T Rowe Associates Inc. MD now owns 7,593,996 shares of the company’s stock valued at $1,770,313,000 after acquiring an additional 897,911 shares in the last quarter. Renaissance Technologies LLC lifted its position in shares of MongoDB by 493.2% in the fourth quarter. Renaissance Technologies LLC now owns 918,200 shares of the company’s stock valued at $180,738,000 after acquiring an additional 763,400 shares in the last quarter. Norges Bank purchased a new stake in shares of MongoDB in the fourth quarter valued at $147,735,000. Finally, Champlain Investment Partners LLC purchased a new position in MongoDB during the first quarter worth about $89,157,000. Institutional investors and hedge funds own 89.22% of the company’s stock.

MongoDB Trading Up 0.4 %

MDB stock opened at $389.99 on Friday. The firm has a fifty day moving average price of $295.63 and a 200 day moving average price of $238.81. MongoDB has a fifty-two week low of $135.15 and a fifty-two week high of $398.89. The company has a debt-to-equity ratio of 1.44, a quick ratio of 4.19 and a current ratio of 4.19. The firm has a market cap of $27.31 billion, a PE ratio of -83.51 and a beta of 1.04.

MongoDB (NASDAQ:MDB – Get Rating) last issued its quarterly earnings results on Thursday, June 1st. The company reported $0.56 earnings per share (EPS) for the quarter, topping analysts’ consensus estimates of $0.18 by $0.38. The company had revenue of $368.28 million during the quarter, compared to the consensus estimate of $347.77 million. MongoDB had a negative return on equity of 43.25% and a negative net margin of 23.58%. MongoDB’s revenue was up 29.0% on a year-over-year basis. During the same period last year, the company earned ($1.15) earnings per share. Sell-side analysts anticipate that MongoDB will post -2.85 earnings per share for the current fiscal year.

MongoDB Company Profile

(Get Rating

MongoDB, Inc provides general purpose database platform worldwide. The company offers MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premise, or in a hybrid environment; and Community Server, a free-to-download version of its database, which includes the functionality that developers need to get started with MongoDB.

Read More

This instant news alert was generated by narrative science technology and financial data from MarketBeat in order to provide readers with the fastest and most accurate reporting. This story was reviewed by MarketBeat’s editorial team prior to publication. Please send any questions or comments about this story to contact@marketbeat.com.

Before you consider MongoDB, you’ll want to hear this.

MarketBeat keeps track of Wall Street’s top-rated and best performing research analysts and the stocks they recommend to their clients on a daily basis. MarketBeat has identified the five stocks that top analysts are quietly whispering to their clients to buy now before the broader market catches on… and MongoDB wasn’t on the list.

While MongoDB currently has a “Moderate Buy” rating among analysts, top-rated analysts believe these five stocks are better buys.

View The Five Stocks Here

Wondering when you’ll finally be able to invest in SpaceX, StarLink or The Boring Company? Click the link below to learn when Elon Musk will let these companies finally IPO.

Get This Free Report

Article originally posted on mongodb google news. Visit mongodb google news

Posted on mongodb google news. Visit mongodb google news

Gulf International Bank UK Ltd cut its holdings in shares of MongoDB, Inc. (NASDAQ:MDB – Get Rating) by 25.4% in the first quarter, according to its most recent disclosure with the Securities and Exchange Commission (SEC). The firm owned 9,066 shares of the company’s stock after selling 3,081 shares during the period. Gulf International Bank UK Ltd’s holdings in MongoDB were worth $2,113,000 as of its most recent filing with the Securities and Exchange Commission (SEC).

Other institutional investors and hedge funds also recently added to or reduced their stakes in the company. Skandinaviska Enskilda Banken AB publ raised its position in shares of MongoDB by 2.5% in the fourth quarter. Skandinaviska Enskilda Banken AB publ now owns 11,467 shares of the company’s stock worth $2,256,000 after acquiring an additional 277 shares during the period. Lindbrook Capital LLC raised its position in shares of MongoDB by 350.0% in the fourth quarter. Lindbrook Capital LLC now owns 171 shares of the company’s stock worth $34,000 after acquiring an additional 133 shares during the period. Principal Financial Group Inc. raised its position in shares of MongoDB by 12.3% in the fourth quarter. Principal Financial Group Inc. now owns 8,452 shares of the company’s stock worth $1,664,000 after acquiring an additional 924 shares during the period. DekaBank Deutsche Girozentrale raised its position in shares of MongoDB by 30.6% in the fourth quarter. DekaBank Deutsche Girozentrale now owns 11,063 shares of the company’s stock worth $2,179,000 after acquiring an additional 2,591 shares during the period. Finally, Los Angeles Capital Management LLC raised its position in shares of MongoDB by 257.8% in the fourth quarter. Los Angeles Capital Management LLC now owns 14,085 shares of the company’s stock worth $2,772,000 after acquiring an additional 10,148 shares during the period. 89.22% of the stock is currently owned by institutional investors and hedge funds.

MongoDB Stock Performance

MongoDB stock opened at $389.99 on Friday. The firm has a 50 day simple moving average of $295.63 and a 200-day simple moving average of $238.81. MongoDB, Inc. has a 1-year low of $135.15 and a 1-year high of $398.89. The company has a debt-to-equity ratio of 1.44, a current ratio of 4.19 and a quick ratio of 4.19. The stock has a market cap of $27.31 billion, a price-to-earnings ratio of -83.51 and a beta of 1.04.

MongoDB (NASDAQ:MDB – Get Rating) last posted its quarterly earnings results on Thursday, June 1st. The company reported $0.56 earnings per share for the quarter, beating the consensus estimate of $0.18 by $0.38. MongoDB had a negative net margin of 23.58% and a negative return on equity of 43.25%. The business had revenue of $368.28 million during the quarter, compared to analysts’ expectations of $347.77 million. During the same quarter in the prior year, the company posted ($1.15) EPS. The business’s revenue for the quarter was up 29.0% on a year-over-year basis. On average, analysts expect that MongoDB, Inc. will post -2.85 EPS for the current year.

Analyst Upgrades and Downgrades

MDB has been the subject of a number of analyst reports. Wedbush decreased their price objective on shares of MongoDB from $240.00 to $230.00 in a research report on Thursday, March 9th. Needham & Company LLC upped their price objective on shares of MongoDB from $250.00 to $430.00 in a research report on Friday, June 2nd. Royal Bank of Canada upped their price target on shares of MongoDB from $400.00 to $445.00 in a research report on Friday. The Goldman Sachs Group upped their price target on shares of MongoDB from $420.00 to $440.00 in a research report on Friday. Finally, KeyCorp upped their price target on shares of MongoDB from $229.00 to $264.00 and gave the stock an “overweight” rating in a research report on Thursday, April 20th. One research analyst has rated the stock with a sell rating, two have issued a hold rating and twenty-one have given a buy rating to the stock. According to data from MarketBeat, the company currently has a consensus rating of “Moderate Buy” and a consensus price target of $349.87.

Insider Activity

In related news, CAO Thomas Bull sold 605 shares of the stock in a transaction that occurred on Monday, April 3rd. The shares were sold at an average price of $228.34, for a total transaction of $138,145.70. Following the completion of the transaction, the chief accounting officer now owns 17,706 shares of the company’s stock, valued at approximately $4,042,988.04. The transaction was disclosed in a filing with the Securities & Exchange Commission, which is accessible through the SEC website. In related news, CRO Cedric Pech sold 720 shares of the stock in a transaction that occurred on Monday, April 3rd. The shares were sold at an average price of $228.33, for a total transaction of $164,397.60. Following the completion of the transaction, the executive now owns 53,050 shares of the company’s stock, valued at approximately $12,112,906.50. The transaction was disclosed in a filing with the Securities & Exchange Commission, which is accessible through the SEC website. Also, CAO Thomas Bull sold 605 shares of the stock in a transaction that occurred on Monday, April 3rd. The stock was sold at an average price of $228.34, for a total transaction of $138,145.70. Following the transaction, the chief accounting officer now directly owns 17,706 shares of the company’s stock, valued at approximately $4,042,988.04. The disclosure for this sale can be found here. Insiders sold a total of 108,856 shares of company stock valued at $27,327,511 in the last 90 days. Company insiders own 4.80% of the company’s stock.

MongoDB Company Profile

(Get Rating)

MongoDB, Inc provides general purpose database platform worldwide. The company offers MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premise, or in a hybrid environment; and Community Server, a free-to-download version of its database, which includes the functionality that developers need to get started with MongoDB.

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AWS has released AWS Signer Container Image Signing (AWS Signer) to provide native AWS support for signing and verifying container images in registries such as Amazon Elastic Container Registry (Amazon ECR). AWS Signer manages code signing certificates, public and private keys, and provides lifecycle management tooling.

Additional features include cross-account signing, signature validity duration, and profile lifecycle management. Cross-account signing allows for signing profiles to be created and managed in restricted accounts reducing the number of individuals with those permissions. Permission can be granted to other accounts as needed to sign artifacts. AWS CloudTrail can be used to provide audit logs of activities within both accounts.

Signature validity periods can be used to create self-expiring profiles. When creating a signing profile, a validity period can be specified; if no validity period is provided a default value of 135 months (the maximum value) is used.

aws signer put-signing-profile 
     --profile-name my_conatiner_signing_profile 
     --platform-id Notation-OCI-SHA384-ECDSA 
     --signature-validity-period value=10, type='MONTHS' 

Profiles can also be canceled or revoked. Canceled profiles are unable to be used to generate new signatures. Revoking the signing profile will invalidate any signatures created after the revocation occurs. This differs from revoking the signature which will cause validation to fail when attempting to deploy a container signed with that signature. Note that revocation is irreversible. The following example shows using the Java SDK to revoke a signature:

package com.examples;

import com.amazonaws.auth.profile.ProfileCredentialsProvider;
import com.amazonaws.services.signer.AWSSigner;
import com.amazonaws.services.signer.AWSSignerClient;
import com.amazonaws.services.signer.model.RevokeSignatureRequest;

public class RevokeSignature {

    public static void main(String[] s) {

        String credentialsProfile = "default";
        String signingJobId = "jobID";
        String revokeReason = "Reason for revocation";

        // Create a client.
        final AWSSigner client = AWSSignerClient.builder()
                .withRegion("region")
                .withCredentials(new ProfileCredentialsProvider(credentialsProfile))
                .build();

        // Revoke a signing job
        client.revokeSignature(new RevokeSignatureRequest()
                .withJobId(signingJobId)
                .withReason(revokeReason));
    }
}

AWS Signer is integrated with Notation, an open-source Cloud Native Computing Foundation (CNCF) Notary project. As described on the Notation GitHub page, Notation can be viewed as providing “similar security to checking git commit signatures, although the signatures are generic and can be used for additional purposes”. Notation makes use of Open Containers Initiative (OCI) distribution features to store signatures and artifacts in the registry with their associated images.

AWS Signer also integrates with AWS Lambda. This allows for workflows where certified code packages can be generated that can be verified by AWS Lambda. The workflow requires the creation of source and destination S3 buckets. AWS Signer can then be used to pull code packages from the source bucket, sign them, and deposit them into the destination bucket.

More details about AWS Signer can be found in the release blog post. At the time of writing AWS Signer can be used with AWS Lambda, Amazon FreeRTOS, AWS IoT Device Management, Amazon ECR, Amazon EKS, AWS Certificate Manager, and CloudTrail. A list of supported regions is available within the AWS documentation.

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Diversified Trust Co has recently made headlines by increasing its holdings in MongoDB, Inc. by an impressive 132% in the 1st quarter of this year. According to its Form 13F filing with the Securities & Exchange Commission, the Nashville-based institutional investor purchased an additional 1,629 shares during that period and now owns a total of 2,863 shares worth $667,000.

For those unfamiliar with MongoDB, it is a worldwide provider of general purpose database platforms. The company’s offerings include MongoDB Atlas, a multi-cloud database-as-a-service solution hosted on their platform; MongoDB Enterprise Advanced, a powerful commercial database server designed for cloud and hybrid environments; and Community Server, which provides free access to MongoDB’s database functionality for developers looking to get started.

Investors have reason to be bullish on this stock as its market cap currently sits at an impressive $27.20 billion. Shares of NASDAQ MDB opened at $388.36 on Friday and have seen a steady increase over the past few months. Its quick and current ratios are both 4.19 which indicates that the company is more than capable of meeting its short-term financial obligations.

Interestingly enough, one may also note that MDB’s debt-to-equity ratio has risen above one point four four. Although this ratio does not necessarily indicate poor financial health for companies in all industries or stages of growth, it demands attention due to the potential risks associated with having higher levels of debt.

Despite these risks associated with higher levels of debt compared to equity, many investors see great potential for growth in MongoDB moving forward. With the industry constantly evolving and expanding in addition to MongoDB’s innovative solutions within data management technology dubbed as highly disruptive by TechRadar Pro magazine earlier this month would interest those who are concerned about cyber-security as well data management issues across various enterprises globally.

As always during these turbulent market conditions, there are no guarantees when investing in new and innovative companies like MongoDB. A robust analysis of the company’s growth potential, financial performance, historical stock movements are recommended to make an informed decision regarding investment. Investing is always a calculated decision, and it requires knowledge commitment in order to succeed long-term.

MongoDB Inc.: A Rising Star in the Tech Industry

MongoDB Inc.: A General Purpose Database Platform

Investing in technology companies has become an attractive trend for many investors looking to diversify their portfolio. One such company with a growing reputation is MongoDB Inc., providing a general purpose database platform worldwide. Among its primary offerings are the hosted multi-cloud database-as-a-service solution called MongoDB Atlas, commercial database server MongoDB Enterprise Advanced and free-to-download version Community Server.

According to recent filings with the SEC, several hedge funds and institutional investors have boosted their stake in MongoDB during the fourth quarter of 2020, citing its potential growth prospects. Bessemer Group Inc., BI Asset Management Fondsmaeglerselskab A S, Lindbrook Capital LLC, Y.D More Investments Ltd and CI Investments Inc are some of the major investors who recently modified their holdings in MongoDB.

Equities analysts covering MDB have given positive ratings to the stock with 21 rating it as ‘buy,’ two rating it as ‘hold’ and one with a ‘sell’ rating. As per Bloomberg.com’s data, the consensus target price of $328.35 suggests moderate buy sentiment among analysts.

The company has reported significant revenue growth in recent years attributed primarily to its core offering – multi-cloud database-as-a-service solution MongoDB Atlas. In Q1 2021, MDB beat analyst earnings expectations by reporting EPS of $0.56 compared to consensus estimates of $0.18.

MongoDB’s incredible success has been echoed by convincing insider expressions through disclosures made by key individuals directly involved with the business such as CTO Mark Porter, CAO Thomas Bull and other top-level executives who sold large amounts of their shares at considerable profits. Despite these exits from company insiders, financially savvy analysts remain bullish on the stock due to its rising industry profile.

Looking towards future growth opportunities, MDB continues to focus on customer feedback enhancements on its existing services while developing new cloud-based products that could significantly compete against rival services provided by Amazon and Google.

In conclusion, MongoDB can provide investors with a unique opportunity to ride upon one of the fastest-growing trends in tech. The company’s growth opportunities look appealing, given its strong financial track record and innovative services. Any investor looking for long-term sustainable gain based on technological developments should keep MDB on their radar.

Article originally posted on mongodb google news. Visit mongodb google news

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In the fast-paced world of data-driven technologies, MongoDB Inc. has emerged as a powerful and flexible database platform.

As organizations seek to unlock the full potential of MongoDB, data modeling and schema design play a pivotal role in ensuring optimal performance and leveraging its unique features.

Industry experts Steve Hoberman (pictured, left), lecturer at Columbia University; Pascal Desmarets (right), founder and chief executive officer at Hackolade (IntegrIT SA/NV); and Daniel Coupal (center), developer advocate at MongoDB, shared their insights in a panel discussion at MongoDB .Local NYC 2023.

“MongoDB is great if you really want to leverage all of its capabilities for complex use cases, complex organizations; you really need to think about your data model so you can best leverage the features of MongoDB,” Desmarets said.

Desmarets, Hoberman and Coupal spoke with theCUBE industry analyst John Furrier at the MongoDB .local NYC event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the significance of data modeling, the evolving landscape of schema design and the role of MongoDB in the AI-driven future. (* Disclosure below.)

Book collaboration and the significance of data modeling in MongoDB

The trio’s expertise and collaboration culminated in the book “MongoDB Data Modeling and Schema Design,” which serves as a resource for data professionals and MongoDB developers. The book primarily caters to two audiences: data professionals experienced in traditional data modeling seeking to apply their skills to MongoDB and developers skilled in MongoDB document development who need guidance on effective data design techniques.

“Steve was teaching relational database for years, wanted to have a Siri on NoSQL databases,” Coupal said. “He has the goal of getting six of them, and he created a core that is used in all the books. For this one, he needed some experts, so he knew Pascal and he got in touch with Pascal. And I received a letter from Steve. We realized that what I’ve been expert in was a good contribution to the book. And we divided the work and went on. To me the collaboration has been absolutely fantastic.”

The trio also discussed the importance of data modeling and schema design in MongoDB. The company’s document model is a differentiator, allowing data storage in JSON format, which is flexible and developer-friendly. However, Desmarets cautioned against assuming that MongoDB’s simplicity implies the ability to build complex systems without thoughtful data modeling. Proper data modeling is essential to leverage MongoDB’s capabilities effectively.

“The danger is that it looks so simple that … it’s deceptive,” he added. “People get the wrong idea that they can build very complex things without really thinking it through.”

The role of data modeling in an AI-driven future

The conversation also addressed the evolving landscape of data modeling, particularly the shift from the old school to the new school. While schema design was previously associated with rigid, normalized structures, MongoDB’s document model allows for more flexibility and schema-less design.

Best of all, MongoDB is conducive to AI applications. It enables the discovery of unexpected relationships within the data, paving the way for auto-schema creation and pattern recognition. With data becoming the lifeblood of companies, data modelers are recognizing the power and significance of their role. They are the unsung heroes laying the foundation for successful data-driven systems and applications, according to Hoberman.

“I know from my perspective, how I’ve been using tools like these language learning models, one is I use them to come up with better definitions,” Hoberman said. “If I’m working with a university and I have a starter definition for a student, I could use these tools to come up with a better definition. Also, when I teach modeling, a lot of what I do is question and answer. Possibly a language learning model can do that for me.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the MongoDB .local NYC event:

(* Disclosure: TheCUBE is a paid media partner for the MongoDB .local NYC event. Neither MongoDB Inc., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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Making affordable models to match Big Tech’s capabilities

We’re at the end of an era, one in which giant tech companies race one another to build the largest language model they can. For a long time, we’ve chased ever-larger models with an increasing number of parameters, culminating in OpenAI’s GPT-4, rumoured to contain over 1 trillion parameters.

Large language models (LLMs) like GPT-4 and LLaMA 2, produced by Big Tech giants like Microsoft-backed OpenAI and Meta, have significant and wide-ranging applications for enterprises and individuals alike. However, the cost incurred by training and running these models has become impossible to ignore, writes Victor Botev, CTO and co-founder of Iris.ai.

We need smarter, optimised model architectures to make AI something that all businesses can access for their own needs. Fortunately, there are a variety of ways for smaller organisations to build cost-effective AI that competes with the capabilities of the largest models.

Tackling the cost issue

For most enterprises, but especially for small to medium-sized operations, the amount of spare capital available for investment in AI can be small. If we want AI to be accessible for the vast majority of organisations, we must make its training and running costs feasible.

Right now, fine-tuning and instruction set tuning a model like GPT-4 for a business to apply to a specific use case might cost tens of thousands of dollars. Quite aside from the training costs, the more complicated your model, the more expensive it is to run over time. At the extreme end, there are estimates that it can cost around $700,000 per day to keep ChatGPT’s servers running.

These issues make customising the largest models for domain-specific use cases totally out of reach for many organisations. So, let’s examine how developers can overcome this issue and create truly cost-effective models.

Training and tuning your AI models

One of the most common approaches to creating a language model is to take an existing, open-source model and train it to fit an organisation’s requirements. When we think about how we can customise these models to reduce running and training costs, it’s essential to know the minimum number of parameters and tuning required for each use case.

Companies today must be able to do three types of model tuning to make them fit for purpose. From the most intricate to the highest level, these are fine-tuning, instruction set tuning, and prompt tuning.

Fine-tuning

Fine-tuning means making minor adjustments to the way models understand and encode the language related to a particular domain. If certain tokens are underrepresented, fine-tuning helps us change this and improve the model’s contextual understanding.  Say that a model has been created with the goal of recognising and categorising scientific papers, for instance, this may make it a good candidate to fine-tune for patent research.

With a carefully selected data set, often involving a business’s own proprietary data, the new model can be far more accurate than the generic model from which it evolved. By focusing on quality over quantity, we can improve accuracy whilst keeping total training time down.

 Instruction set tuning

Instruction set tuning and prompt tuning are less expensive and data-intensive than fine-tuning but require us to take more care in how we formulate the instructions and prompts. Another challenge for both of these approaches is working out how we automate data gathering to make this a scalable process.

Instruction set tuning is a slightly newer technique, introduced in 2021 with the ‘Finetuned Language Models Are Zero-Shot Learners’ paper from Google researchers. It involves giving the model an understanding of certain instructions – instead of the user having to tell it how to follow an instruction step-by-step.

This approach does have some other limitations – namely, how we deal with performance losses due to counterproductive or overlapping instructions. To overcome this, you need highly tailored, well-curated datasets with instructions that don’t overlap – normally, you would need to create and curate these datasets manually. However, by using a ‘swarm’ of smarter, specialised language models, you can automatically generate high-quality datasets and save human labour in the process.

Prompt tuning

When it comes to prompt tuning, we can turn our attention to how we extract the exact knowledge we want from a model based on how it’s been encoded. A useful parallel may be how you phrase a search engine query to get the right results. As we zoom out to this high-level optimisation, bear in mind that prompt tuning’s effectiveness is dependent on how much fine-tuning and instruction tuning remains to be done.

If the knowledge you want to extract from the model has been encoded properly, then no fine-tuning will be required. But language has different meanings in different contexts, so fine-tuning will often be required to optimise a model for specialised domains. Similarly, if a model is able to carry out multi-step instructions and present knowledge to the user in an easily understandable way, then no instruction tuning will be needed.

How many parameters do you need?

Defining a model as having ‘X billion parameters’ means simply that this number of parameters are activated every time it responds. Whilst, in an ideal world, this correlates to a better, more fine-tuned response, we must consider how many parameters are needed for each specific use case.

To make models cost-efficient, we cannot fall into the trap of treating size and capability as a linear progression. We must search for smarter, optimised architectures, not just apply brute force to each use case.

Developers should examine the task, or set of tasks, for which they’re creating an AI model. If it’s a language model, they should consider if it needs to be particularly good at a certain element of natural language processing: such as sentence boundary disambiguation, factual validation, or part-of-speech tagging. `This information will reveal which areas of the architecture demand additional focus, and which areas can be simplified.

To make a viable asset, you need to be able to do fine-tuning, instruction set tuning, and prompt tuning relatively inexpensively. This creates a ‘temperate zone’ for the required number of parameters. Any lower than a couple of billion parameters and performance will suffer. Anything above that and the price point gets out of reach for smaller businesses. As with any resource-intensive project, balance is key.

Make the data work for you, not against you

The idea of ‘data-centric AI’, championed by industry figureheads such as Andrew Ng, posits that we must focus on data quality over quantity. As our algorithms have progressed, and we have access to incredible open-source LLMs to train our own models, it’s time to focus on how we engineer the data to build a cost-efficient model without sacrificing performance – with corporations like Microsoft already working in this direction with Phi-1.

Focus on the collection of high-quality, curated datasets for fine-tuning, ensuring high accuracy and low chances of hallucination whilst cutting down on total training time. In the future, synthetic datasets may become a viable option, allowing us to source the required amount of data for even the most niche domains.

To make AI financially viable for smaller organisations, we must create smarter language models that only consume the necessary amount of power. Once we do that, we’re well on the way to democratising AI and making it accessible for everyone, no matter how specialised or complex their domain.

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