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Git 2.37 Brings Builtin File Monitor, Improved Pruning, and More

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MMS Sergio De Simone

Article originally posted on InfoQ. Visit InfoQ

Git 2.37 brings many new ans improved features, including a builtin file system monitor on Windows and macOS, better unreachable objects management, improved external diff, faster git add, and more.

Git’s new builtin file monitor aims to improve performance when accessing the file system to detect file changes. This may reduce the time required to execute git status and other commands. Git has supported the possibility of hooking tools like Watchman since version 2.16. This option was not easy to configure, though, and not frequently used. Instead, you can now enable the builtin file monitor by using the following configuration option:

git config core.fsmonitor true

According to Jeff Hostetler, the author of the patches for git’s new file monitor, the implementation relies mostly on cross-platform code with custom backends leveraging OS-native features, i.e. FSEvents on macOS and ReadDirectoryChangesW on Windows. A Linux backend would probably use either inotify or fanotify, Hostetler says, but that work has not started yet.

To improve pruning performance, git 2.73 introduces cruft packs, aimed to reduce the chance of data races when removing unreachable objects.

Unreachable objects aren’t removed immediately, since doing so could race with an incoming push which may reference an object which is about to be deleted. Instead, those unreachable objects are stored as loose objects and stay that way until they are older than the expiration window, at which point they are removed by git-prune.

Unreachable objects that have not left their grace period tend to accumulate and enlarge .git/objects. This can lead to decreased performance and in extreme cases to inode starvation and performance degradation of the whole system.

Cruft packs eliminate the need to store unreachable objects in loose files and instead consolidate them in a single packfile between successive prune operations along with a timestamp file to track grace periods.

Another improvement in git 2.73 deals with diff temp files. Instead of using loose files, diffs are now generated inside a temporary directory under the same basename, using mks_tempfile_ts. This allows the files to have arbitrary names, each in their own separate directory. The main benefit this brings in is with graphical diff programs, that may display a nicer output.

As mentioned, git 2.73 also include improved performance for select commands, such as git add -i, which was rewritten in C from Perl and been under testing for a while. The latest git version adopts the new C implementation as a default.

As a final note, many developers will welcome the new git -v and git -h options, which will be interpreted as git --version and git --help respectively. Interestingly, while apparently a no-brainer, this patch still required some discussion.

Git 2.73 includes many more changes than can be covered here, so do not miss the official release note for the full detail. Additionally, you can also check out GitHub’s and GitKraken’s takes on what is most relevant in the new release.

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How to deploy CouchDB as a cluster with Docker | TechRepublic

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Recently, I showed you how to deploy CouchDB as a standalone NoSQL database server, which could serve you well in small instances. This time around, I want to show you a neat trick for deploying CouchDB as a cluster using Docker. Although this method might not be ideal for production usage, it’s a great way for developers to be able to work with CouchDB in a test environment.

Without further ado, let’s get to the deployment.

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What you’ll need

To make this work, you’ll need a server with an OS that supports Docker. I’ll demonstrate with Ubuntu Server 22.04, but you can use whichever platform you’re comfortable with.

How to install Docker

On the off-chance you don’t already have Docker installed, here’s how you do it.

First, add the official Docker GPG key with the command:

curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg

Next, add the required repository:

echo "deb [arch=amd64 signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null

Install the required dependencies with:

sudo apt-get install apt-transport-https ca-certificates curl gnupg lsb-release -y

Finally, we can install the latest version of the Docker engine:

sudo apt-get update

sudo apt-get install docker-ce docker-ce-cli containerd.io -y

Add your user to the docker group with the command:

sudo usermod -aG docker $USER

Make the system aware of the change with:

newgrp docker

How to deploy the CouchDB containers

We’re going to deploy three CouchDB containers, each using a unique external port. The first will use port 5984 and is deployed with:

docker run -itd -p 5984:5984 -p 5986:5986 --name=couchdb0 -e NODENAME='couchdb-0.local.com' --mount 'source=volume-0,target=/opt/couchdb/data' couchdb:2.3.0

The second container is deployed (using port 15984) with:

docker run -itd -p 15984:5984 -p 15986:5986 --name=couchdb1 -e  NODENAME='couchdb-1.local.com' --mount 'source=volume-1,target=/opt/couchdb/data' couchdb:2.3.0

The final container is deployed *using port 25984) with:

docker run -itd -p 25984:5984 -p 25986:5986 --name=couchdb2 -e NODENAME='couchdb-2.local.com' --mount 'source=volume-2,target=/opt/couchdb/data' couchdb:2.3.0

If you issue the command docker ps -a | grep couchdb you should see all three instances up and running.

How to create the administrator user

We now need to create an administrator on each container. In each instance, replace PASSWORD with a strong password (make sure it’s the same for each). The commands for this will be:

curl -X PUT http://localhost:5984/_node/couchdb@couchdb-0.local.com/_config/admins/admin -d '"PASSWORD"
curl -X PUT http://localhost:15984/_node/couchdb@couchdb-1.local.com/_config/admins/admin -d '"PASSWORD"
curl -X PUT http://localhost:25984/_node/couchdb@couchdb-2.local.com/_config/admins/admin -d '"PASSWORD"''

Outstanding. Let’s continue.

How to create a Docker network

At the moment, the CouchDB nodes have no awareness of one another. To fix that we need to create a new Docker network. Do this with:

docker network create -d bridge --subnet 172.25.0.0/16 isolated_nw

With our network created, we now have to connect our containers to it, which is done using the following commands:

docker network connect --alias couchdb-0.local.com isolated_nw couchdb0
docker network connect --alias couchdb-1.local.com isolated_nw couchdb1
docker network connect --alias couchdb-2.local.com isolated_nw couchdb2

Perfect.

How to log into the admin console

Open a web browser and point it to http://server:5984, where SERVER is the IP address of the server hosting Docker. Log in with the username admin and the password you added for the admin user earlier.

Once you’ve logged in, click the wrench icon in the left navigation and then click Configure a Cluster (Figure A).

Figure A

The CouchDB Setup window.

In the resulting window (Figure B), you’ll need to fill in the admin credentials and then add a node to the cluster.

Figure B

The CouchDB cluster configuration window.

To add the first node to the cluster, you’ll type couchdb-1.local.com as the Remote Host and leave the port at 5984. Once you’ve done that, click Add Node. Do the same thing for the second node using couchdb-2.local.com as the Remote Host.

After adding both nodes, click Configure Cluster and you should be rewarded with a page informing you the cluster has been configured (Figure C).

Figure C

The cluster is up and running.

Congratulations, you’ve just deployed your first CouchDB cluster, with the help of Docker.

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MongoDB Inc. (MDB): Don't ignore this Blaring Warning Signal – Invest Chronicle

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For the readers interested in the stock health of MongoDB Inc. (MDB). It is currently valued at $262.01. When the transactions were called off in the previous session, Stock hit the highs of $281.274, after setting-off with the price of $274.88. Company’s stock value dipped to $268.4701 during the trading on the day. When the trading was stopped its value was $276.77.Recently in News on June 7, 2022, Ninth Annual MongoDB Innovation Award Winners Unveiled at MongoDB World 2022. MongoDB, Inc. (NASDAQ: MDB), today announced the fifteen winners of the ninth annual MongoDB Innovation Awards. The winners are being honored during MongoDB World 2022, happening in New York City at the Javits Center, June 7-9, 2022. You can read further details here

MongoDB Inc. had a pretty Dodgy run when it comes to the market performance. The 1-year high price for the company’s stock is recorded $519.54 on 01/03/22, with the lowest value was $213.39 for the same time period, recorded on 05/26/22.

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MongoDB Inc. (MDB) full year performance was -27.87%

Price records that include history of low and high prices in the period of 52 weeks can tell a lot about the stock’s existing status and the future performance. Presently, MongoDB Inc. shares are logging -55.59% during the 52-week period from high price, and 22.78% higher than the lowest price point for the same timeframe. The stock’s price range for the 52-week period managed to maintain the performance between $213.39 and $590.00.

The company’s shares, operating in the sector of Technology managed to top a trading volume set approximately around 782283 for the day, which was evidently lower, when compared to the average daily volumes of the shares.

When it comes to the year-to-date metrics, the MongoDB Inc. (MDB) recorded performance in the market was -47.72%, having the revenues showcasing -36.50% on a quarterly basis in comparison with the same period year before. At the time of this writing, the total market value of the company is set at 18.08B, as it employees total of 3544 workers.

Analysts verdict on MongoDB Inc. (MDB)

During the last month, 0 analysts gave the MongoDB Inc. a BUY rating, 0 of the polled analysts branded the stock as an OVERWEIGHT, 0 analysts were recommending to HOLD this stock, 0 of them gave the stock UNDERWEIGHT rating, and 0 of the polled analysts provided SELL rating.

According to the data provided on Barchart.com, the moving average of the company in the 100-day period was set at 339.20, with a change in the price was noted -144.33. In a similar fashion, MongoDB Inc. posted a movement of -35.76% for the period of last 100 days, recording 1,549,043 in trading volumes.

Total Debt to Equity Ratio (D/E) can also provide valuable insight into the company’s financial health and market status. The debt to equity ratio can be calculated by dividing the present total liabilities of a company by shareholders’ equity. Debt to Equity thus makes a valuable metrics that describes the debt, company is using in order to support assets, correlating with the value of shareholders’ equity The total Debt to Equity ratio for MDB is recording 1.77 at the time of this writing. In addition, long term Debt to Equity ratio is set at 1.76.

MongoDB Inc. (MDB): Technical Analysis

Raw Stochastic average of MongoDB Inc. in the period of last 50 days is set at 22.08%. The result represents downgrade in oppose to Raw Stochastic average for the period of the last 20 days, recording 33.86%. In the last 20 days, the company’s Stochastic %K was 48.71% and its Stochastic %D was recorded 63.23%.

Let’s take a glance in the erstwhile performances of MongoDB Inc., multiple moving trends are noted. Year-to-date Price performance of the company’s stock appears to be encouraging, given the fact the metric is recording -47.72%. Additionally, trading for the stock in the period of the last six months notably deteriorated by -48.94%, alongside a downfall of -27.87% for the period of the last 12 months. The shares increased approximately by 3.57% in the 7-day charts and went down by 10.68% in the period of the last 30 days. Common stock shares were lifted by -36.50% during last recorded quarter.

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Database Software Market Size, Scope and Forecast | Teradata, MongoDB, Mark Logic …

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Posted on mongodb google news. Visit mongodb google news

New Jersey, United States – This Database Software Market research examines the state and future prospects of the Database Software market from the perspectives of competitors, regions, products, and end Applications/industries. The Worldwide Database Software market is segmented by product and Application/end industries in this analysis, which also analyses the different players in the global and key regions.

The analysis for the Database Software market is included in this report in its entirety. The in-depth secondary research, primary interviews, and internal expert reviews went into the Database Software report’s market estimates. These market estimates were taken into account by researching the effects of different social, political, and economic aspects, as well as the present market dynamics, on the growth of the Database Software market.

Get Full PDF Sample Copy of Report: (Including Full TOC, List of Tables & Figures, Chart) @ https://www.verifiedmarketresearch.com/download-sample/?rid=85913

Key Players Mentioned in the Database Software Market Research Report:

Teradata, MongoDB, Mark Logic, Couch base, SQLite, Datastax, InterSystems, MariaDB, Science Soft, AI Software.

The Porter’s Five Forces analysis, which explains the five forces: customer’s bargaining power, distributor’s bargaining power, the threat of substitute products, and degree of competition in the Database Software Market, is included in the report along with the market overview, which includes the market dynamics. It describes the different players who make up the market ecosystem, including system integrators, middlemen, and end-users. The competitive environment of the Database Software market is another major topic of the report. For enhanced decision-making, the research also provides in-depth details regarding the COVID-19 scenario and its influence on the market.

Database Software Market Segmentation:  

Database Software Market, By Type of Product

• Database Maintenance Management
• Database Operation Management

Database Software Market, By End User

• BFSI
• IT & Telecom
• Media & Entertainment
• Healthcare

Inquire for a Discount on this Premium Report @ https://www.verifiedmarketresearch.com/ask-for-discount/?rid=85913

Database Software Market Report Scope 

ATTRIBUTES DETAILS
ESTIMATED YEAR 2022
BASE YEAR 2021
FORECAST YEAR 2029
HISTORICAL YEAR 2020
UNIT Value (USD Million/Billion)
SEGMENTS COVERED Types, Applications, End-Users, and more.
REPORT COVERAGE Revenue Forecast, Company Ranking, Competitive Landscape, Growth Factors, and Trends
BY REGION North America, Europe, Asia Pacific, Latin America, Middle East and Africa
CUSTOMIZATION SCOPE Free report customization (equivalent up to 4 analysts working days) with purchase. Addition or alteration to country, regional & segment scope.

Key questions answered in the report: 

1. Which are the five top players of the Database Software market?

2. How will the Database Software market change in the next five years?

3. Which product and application will take a lion’s share of the Database Software market?

4. What are the drivers and restraints of the Database Software market?

5. Which regional market will show the highest growth?

6. What will be the CAGR and size of the Database Software market throughout the forecast period?

For More Information or Query or Customization Before Buying, Visit @ https://www.verifiedmarketresearch.com/product/database-software-market/ 

Visualize Database Software Market using Verified Market Intelligence:- 

Verified Market Intelligence is our BI-enabled platform for narrative storytelling of this market. VMI offers in-depth forecasted trends and accurate Insights on over 20,000+ emerging & niche markets, helping you make critical revenue-impacting decisions for a brilliant future. 

VMI provides a holistic overview and global competitive landscape with respect to Region, Country, and Segment, and Key players of your market. Present your Market Report & findings with an inbuilt presentation feature saving over 70% of your time and resources for Investor, Sales & Marketing, R&D, and Product Development pitches. VMI enables data delivery In Excel and Interactive PDF formats with over 15+ Key Market Indicators for your market. 

Visualize Database Software Market using VMI @ https://www.verifiedmarketresearch.com/vmintelligence/ 

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Verified Market Research® is a leading Global Research and Consulting firm that has been providing advanced analytical research solutions, custom consulting and in-depth data analysis for 10+ years to individuals and companies alike that are looking for accurate, reliable and up to date research data and technical consulting. We offer insights into strategic and growth analyses, Data necessary to achieve corporate goals and help make critical revenue decisions. 

Our research studies help our clients make superior data-driven decisions, understand market forecast, capitalize on future opportunities and optimize efficiency by working as their partner to deliver accurate and valuable information. The industries we cover span over a large spectrum including Technology, Chemicals, Manufacturing, Energy, Food and Beverages, Automotive, Robotics, Packaging, Construction, Mining & Gas. Etc. 

We, at Verified Market Research, assist in understanding holistic market indicating factors and most current and future market trends. Our analysts, with their high expertise in data gathering and governance, utilize industry techniques to collate and examine data at all stages. They are trained to combine modern data collection techniques, superior research methodology, subject expertise and years of collective experience to produce informative and accurate research. 

Having serviced over 5000+ clients, we have provided reliable market research services to more than 100 Global Fortune 500 companies such as Amazon, Dell, IBM, Shell, Exxon Mobil, General Electric, Siemens, Microsoft, Sony and Hitachi. We have co-consulted with some of the world’s leading consulting firms like McKinsey & Company, Boston Consulting Group, Bain and Company for custom research and consulting projects for businesses worldwide. 

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MongoDB Sees Unusually High Options Volume (NASDAQ:MDB) – MarketBeat

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MongoDB, Inc. (NASDAQ:MDBGet Rating) was the target of some unusual options trading on Wednesday. Investors purchased 23,831 put options on the company. This represents an increase of approximately 2,157% compared to the typical volume of 1,056 put options.

In other news, Director Dwight A. Merriman sold 3,000 shares of the business’s stock in a transaction on Wednesday, June 1st. The stock was sold at an average price of $251.74, for a total value of $755,220.00. Following the completion of the transaction, the director now owns 544,896 shares in the company, valued at $137,172,119.04. The transaction was disclosed in a document filed with the Securities & Exchange Commission, which can be accessed through the SEC website. Also, CEO Dev Ittycheria sold 35,000 shares of the business’s stock in a transaction on Wednesday, April 6th. The stock was sold at an average price of $412.38, for a total value of $14,433,300.00. Following the completion of the transaction, the chief executive officer now owns 204,744 shares of the company’s stock, valued at approximately $84,432,330.72. The disclosure for this sale can be found here. Insiders have sold 87,309 shares of company stock valued at $31,453,225 in the last quarter. 5.70% of the stock is owned by company insiders.

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A number of hedge funds and other institutional investors have recently modified their holdings of MDB. Allspring Global Investments Holdings LLC bought a new stake in MongoDB during the 4th quarter valued at $674,390,000. Norges Bank bought a new position in shares of MongoDB in the 4th quarter worth $277,934,000. TD Asset Management Inc. raised its position in shares of MongoDB by 153.9% in the 4th quarter. TD Asset Management Inc. now owns 525,000 shares of the company’s stock worth $277,909,000 after acquiring an additional 318,259 shares in the last quarter. Jennison Associates LLC bought a new position in shares of MongoDB in the 1st quarter worth $113,395,000. Finally, 1832 Asset Management L.P. raised its position in shares of MongoDB by 19.3% in 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 in the last quarter. 88.70% of the stock is owned by institutional investors and hedge funds.

Shares of MongoDB stock traded down $23.34 on Thursday, reaching $253.43. The company had a trading volume of 11,444 shares, compared to its average volume of 1,514,970. The firm has a market cap of $17.26 billion, a price-to-earnings ratio of -52.38 and a beta of 1.00. The company has a debt-to-equity ratio of 1.69, a current ratio of 4.16 and a quick ratio of 4.16. The firm’s 50-day moving average price is $282.15 and its two-hundred day moving average price is $370.25. MongoDB has a 1 year low of $213.39 and a 1 year high of $590.00.

MongoDB (NASDAQ:MDBGet Rating) last posted its quarterly earnings data on Wednesday, June 1st. The company reported $0.20 earnings per share (EPS) for the quarter, beating analysts’ consensus estimates of ($1.34) by $1.54. The company had revenue of $285.45 million during the quarter, compared to analysts’ expectations of $267.10 million. MongoDB had a negative return on equity of 45.56% and a negative net margin of 32.75%. MongoDB’s revenue was up 57.1% compared to the same quarter last year. During the same quarter in the previous year, the business earned ($0.98) EPS. As a group, analysts anticipate that MongoDB will post -5.09 EPS for the current year.

Several analysts recently commented on the company. Piper Sandler cut their price objective on MongoDB from $585.00 to $430.00 and set an “overweight” rating for the company in a report on Thursday, June 2nd. Stifel Nicolaus cut their price target on MongoDB from $425.00 to $340.00 in a report on Thursday, June 2nd. Morgan Stanley cut their price target on MongoDB from $378.00 to $368.00 and set an “overweight” rating for the company in a report on Thursday, June 2nd. Citigroup boosted their price target on MongoDB from $405.00 to $425.00 in a report on Thursday, June 2nd. Finally, Redburn Partners initiated coverage on MongoDB in a report on Wednesday. They set a “sell” rating and a $190.00 price target for the company. One investment analyst has rated the stock with a sell rating, one has assigned a hold rating and fifteen have given a buy rating to the stock. Based on data from MarketBeat.com, the stock presently has an average rating of “Moderate Buy” and a consensus target price of $406.82.

About MongoDB (Get Rating)

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.

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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 [email protected]

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NoSQL Database Market Size, Scope and Forecast | Objectivity Inc, Neo Technology Inc …

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New Jersey, United States – This NoSQL Database Market research examines the state and future prospects of the NoSQL Database market from the perspectives of competitors, regions, products, and end Applications/industries. The Worldwide NoSQL Database market is segmented by product and Application/end industries in this analysis, which also analyses the different players in the global and key regions.

The analysis for the NoSQL Database market is included in this report in its entirety. The in-depth secondary research, primary interviews, and internal expert reviews went into the NoSQL Database report’s market estimates. These market estimates were taken into account by researching the effects of different social, political, and economic aspects, as well as the present market dynamics, on the growth of the NoSQL Database market.

Get Full PDF Sample Copy of Report: (Including Full TOC, List of Tables & Figures, Chart) @ https://www.verifiedmarketresearch.com/download-sample/?rid=129411

Key Players Mentioned in the NoSQL Database Market Research Report:

Objectivity Inc, Neo Technology Inc, MongoDB Inc, MarkLogic Corporation, Google LLC, Couchbase Inc, Microsoft Corporation, DataStax Inc, Amazon Web Services Inc & Aerospike Inc.

The Porter’s Five Forces analysis, which explains the five forces: customer’s bargaining power, distributor’s bargaining power, the threat of substitute products, and degree of competition in the NoSQL Database Market, is included in the report along with the market overview, which includes the market dynamics. It describes the different players who make up the market ecosystem, including system integrators, middlemen, and end-users. The competitive environment of the NoSQL Database market is another major topic of the report. For enhanced decision-making, the research also provides in-depth details regarding the COVID-19 scenario and its influence on the market.

NoSQL Database Market Segmentation:  

NoSQL Database Market, By Type

• Graph Database
• Column Based Store
• Document Database
• Key-Value Store

NoSQL Database Market, By Application

• Web Apps
• Data Analytics
• Mobile Apps
• Metadata Store
• Cache Memory
• Others

NoSQL Database Market, By Industry Vertical

• Retail
• Gaming
• IT
• Others

Inquire for a Discount on this Premium Report @ https://www.verifiedmarketresearch.com/ask-for-discount/?rid=129411

NoSQL Database Market Report Scope 

ATTRIBUTES DETAILS
ESTIMATED YEAR 2022
BASE YEAR 2021
FORECAST YEAR 2029
HISTORICAL YEAR 2020
UNIT Value (USD Million/Billion)
SEGMENTS COVERED Types, Applications, End-Users, and more.
REPORT COVERAGE Revenue Forecast, Company Ranking, Competitive Landscape, Growth Factors, and Trends
BY REGION North America, Europe, Asia Pacific, Latin America, Middle East and Africa
CUSTOMIZATION SCOPE Free report customization (equivalent up to 4 analysts working days) with purchase. Addition or alteration to country, regional & segment scope.

Key questions answered in the report: 

1. Which are the five top players of the NoSQL Database market?

2. How will the NoSQL Database market change in the next five years?

3. Which product and application will take a lion’s share of the NoSQL Database market?

4. What are the drivers and restraints of the NoSQL Database market?

5. Which regional market will show the highest growth?

6. What will be the CAGR and size of the NoSQL Database market throughout the forecast period?

For More Information or Query or Customization Before Buying, Visit @ https://www.verifiedmarketresearch.com/product/nosql-database-market/ 

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VMI provides a holistic overview and global competitive landscape with respect to Region, Country, and Segment, and Key players of your market. Present your Market Report & findings with an inbuilt presentation feature saving over 70% of your time and resources for Investor, Sales & Marketing, R&D, and Product Development pitches. VMI enables data delivery In Excel and Interactive PDF formats with over 15+ Key Market Indicators for your market. 

Visualize NoSQL Database Market using VMI @ https://www.verifiedmarketresearch.com/vmintelligence/ 

About Us: Verified Market Research® 

Verified Market Research® is a leading Global Research and Consulting firm that has been providing advanced analytical research solutions, custom consulting and in-depth data analysis for 10+ years to individuals and companies alike that are looking for accurate, reliable and up to date research data and technical consulting. We offer insights into strategic and growth analyses, Data necessary to achieve corporate goals and help make critical revenue decisions. 

Our research studies help our clients make superior data-driven decisions, understand market forecast, capitalize on future opportunities and optimize efficiency by working as their partner to deliver accurate and valuable information. The industries we cover span over a large spectrum including Technology, Chemicals, Manufacturing, Energy, Food and Beverages, Automotive, Robotics, Packaging, Construction, Mining & Gas. Etc. 

We, at Verified Market Research, assist in understanding holistic market indicating factors and most current and future market trends. Our analysts, with their high expertise in data gathering and governance, utilize industry techniques to collate and examine data at all stages. They are trained to combine modern data collection techniques, superior research methodology, subject expertise and years of collective experience to produce informative and accurate research. 

Having serviced over 5000+ clients, we have provided reliable market research services to more than 100 Global Fortune 500 companies such as Amazon, Dell, IBM, Shell, Exxon Mobil, General Electric, Siemens, Microsoft, Sony and Hitachi. We have co-consulted with some of the world’s leading consulting firms like McKinsey & Company, Boston Consulting Group, Bain and Company for custom research and consulting projects for businesses worldwide. 

Contact us:

Mr. Edwyne Fernandes

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NoSQL Database Market Size, Scope and Forecast | Objectivity Inc, Neo Technology Inc …

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Posted on mongodb google news. Visit mongodb google news

New Jersey, United States – This NoSQL Database Market research examines the state and future prospects of the NoSQL Database market from the perspectives of competitors, regions, products, and end Applications/industries. The Worldwide NoSQL Database market is segmented by product and Application/end industries in this analysis, which also analyses the different players in the global and key regions.

The analysis for the NoSQL Database market is included in this report in its entirety. The in-depth secondary research, primary interviews, and internal expert reviews went into the NoSQL Database report’s market estimates. These market estimates were taken into account by researching the effects of different social, political, and economic aspects, as well as the present market dynamics, on the growth of the NoSQL Database market.

Get Full PDF Sample Copy of Report: (Including Full TOC, List of Tables & Figures, Chart) @ https://www.verifiedmarketresearch.com/download-sample/?rid=129411

Key Players Mentioned in the NoSQL Database Market Research Report:

Objectivity Inc, Neo Technology Inc, MongoDB Inc, MarkLogic Corporation, Google LLC, Couchbase Inc, Microsoft Corporation, DataStax Inc, Amazon Web Services Inc & Aerospike Inc.

The Porter’s Five Forces analysis, which explains the five forces: customer’s bargaining power, distributor’s bargaining power, the threat of substitute products, and degree of competition in the NoSQL Database Market, is included in the report along with the market overview, which includes the market dynamics. It describes the different players who make up the market ecosystem, including system integrators, middlemen, and end-users. The competitive environment of the NoSQL Database market is another major topic of the report. For enhanced decision-making, the research also provides in-depth details regarding the COVID-19 scenario and its influence on the market.

NoSQL Database Market Segmentation:  

NoSQL Database Market, By Type

• Graph Database
• Column Based Store
• Document Database
• Key-Value Store

NoSQL Database Market, By Application

• Web Apps
• Data Analytics
• Mobile Apps
• Metadata Store
• Cache Memory
• Others

NoSQL Database Market, By Industry Vertical

• Retail
• Gaming
• IT
• Others

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NoSQL Database Market Report Scope 

ATTRIBUTES DETAILS
ESTIMATED YEAR 2022
BASE YEAR 2021
FORECAST YEAR 2029
HISTORICAL YEAR 2020
UNIT Value (USD Million/Billion)
SEGMENTS COVERED Types, Applications, End-Users, and more.
REPORT COVERAGE Revenue Forecast, Company Ranking, Competitive Landscape, Growth Factors, and Trends
BY REGION North America, Europe, Asia Pacific, Latin America, Middle East and Africa
CUSTOMIZATION SCOPE Free report customization (equivalent up to 4 analysts working days) with purchase. Addition or alteration to country, regional & segment scope.

Key questions answered in the report: 

1. Which are the five top players of the NoSQL Database market?

2. How will the NoSQL Database market change in the next five years?

3. Which product and application will take a lion’s share of the NoSQL Database market?

4. What are the drivers and restraints of the NoSQL Database market?

5. Which regional market will show the highest growth?

6. What will be the CAGR and size of the NoSQL Database market throughout the forecast period?

For More Information or Query or Customization Before Buying, Visit @ https://www.verifiedmarketresearch.com/product/nosql-database-market/ 

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Verified Market Intelligence is our BI-enabled platform for narrative storytelling of this market. VMI offers in-depth forecasted trends and accurate Insights on over 20,000+ emerging & niche markets, helping you make critical revenue-impacting decisions for a brilliant future. 

VMI provides a holistic overview and global competitive landscape with respect to Region, Country, and Segment, and Key players of your market. Present your Market Report & findings with an inbuilt presentation feature saving over 70% of your time and resources for Investor, Sales & Marketing, R&D, and Product Development pitches. VMI enables data delivery In Excel and Interactive PDF formats with over 15+ Key Market Indicators for your market. 

Visualize NoSQL Database Market using VMI @ https://www.verifiedmarketresearch.com/vmintelligence/ 

About Us: Verified Market Research® 

Verified Market Research® is a leading Global Research and Consulting firm that has been providing advanced analytical research solutions, custom consulting and in-depth data analysis for 10+ years to individuals and companies alike that are looking for accurate, reliable and up to date research data and technical consulting. We offer insights into strategic and growth analyses, Data necessary to achieve corporate goals and help make critical revenue decisions. 

Our research studies help our clients make superior data-driven decisions, understand market forecast, capitalize on future opportunities and optimize efficiency by working as their partner to deliver accurate and valuable information. The industries we cover span over a large spectrum including Technology, Chemicals, Manufacturing, Energy, Food and Beverages, Automotive, Robotics, Packaging, Construction, Mining & Gas. Etc. 

We, at Verified Market Research, assist in understanding holistic market indicating factors and most current and future market trends. Our analysts, with their high expertise in data gathering and governance, utilize industry techniques to collate and examine data at all stages. They are trained to combine modern data collection techniques, superior research methodology, subject expertise and years of collective experience to produce informative and accurate research. 

Having serviced over 5000+ clients, we have provided reliable market research services to more than 100 Global Fortune 500 companies such as Amazon, Dell, IBM, Shell, Exxon Mobil, General Electric, Siemens, Microsoft, Sony and Hitachi. We have co-consulted with some of the world’s leading consulting firms like McKinsey & Company, Boston Consulting Group, Bain and Company for custom research and consulting projects for businesses worldwide. 

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MongoDB (NASDAQ:MDB) Coverage Initiated by Analysts at Redburn Partners

MMS Founder
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Posted on mongodb google news. Visit mongodb google news

Redburn Partners began coverage on shares of MongoDB (NASDAQ:MDBGet Rating) in a research note released on Wednesday, MarketBeat.com reports. The firm issued a sell rating and a $190.00 target price on the stock.

Several other research firms have also commented on MDB. Canaccord Genuity Group cut their price objective on MongoDB from $400.00 to $300.00 in a research note on Thursday, June 2nd. William Blair reiterated an outperform rating on shares of MongoDB in a research note on Tuesday, May 24th. Piper Sandler cut their price objective on MongoDB from $585.00 to $430.00 and set an overweight rating for the company in a research note on Thursday, June 2nd. Morgan Stanley dropped their price target on MongoDB from $378.00 to $368.00 and set an overweight rating for the company in a research report on Thursday, June 2nd. Finally, Oppenheimer dropped their price target on MongoDB from $490.00 to $400.00 and set an outperform rating for the company in a research report on Thursday, June 2nd. One equities research analyst has rated the stock with a sell rating, one has assigned a hold rating and fifteen have assigned a buy rating to the stock. According to data from MarketBeat.com, MongoDB presently has a consensus rating of Moderate Buy and a consensus price target of $406.82.

Shares of MongoDB stock opened at $276.77 on Wednesday. The company has a quick ratio of 4.16, a current ratio of 4.16 and a debt-to-equity ratio of 1.69. MongoDB has a twelve month low of $213.39 and a twelve month high of $590.00. The business has a 50-day moving average price of $282.15 and a 200 day moving average price of $370.25. The firm has a market cap of $18.85 billion, a PE ratio of -57.18 and a beta of 1.00.

MongoDB (NASDAQ:MDBGet Rating) last announced its quarterly earnings results on Wednesday, June 1st. The company reported $0.20 earnings per share for the quarter, beating the consensus estimate of ($1.34) by $1.54. MongoDB had a negative return on equity of 45.56% and a negative net margin of 32.75%. The firm had revenue of $285.45 million during the quarter, compared to analyst estimates of $267.10 million. During the same quarter in the previous year, the business earned ($0.98) EPS. MongoDB’s revenue for the quarter was up 57.1% compared to the same quarter last year. On average, sell-side analysts expect that MongoDB will post -5.09 EPS for the current year.

In other MongoDB news, CRO Cedric Pech sold 309 shares of the company’s stock in a transaction on Monday, April 4th. The stock was sold at an average price of $443.77, for a total transaction of $137,124.93. Following the transaction, the executive now directly owns 46,135 shares in the company, valued at $20,473,328.95. The transaction was disclosed in a legal filing with the Securities & Exchange Commission, which can be accessed through the SEC website. Also, Director Dwight A. Merriman sold 14,000 shares of the company’s stock in a transaction on Monday, May 2nd. The stock was sold at an average price of $349.22, for a total value of $4,889,080.00. Following the transaction, the director now owns 1,323,384 shares in the company, valued at $462,152,160.48. The disclosure for this sale can be found here. Insiders sold 87,309 shares of company stock worth $31,453,225 over the last quarter. 5.70% of the stock is currently owned by insiders.

Institutional investors have recently bought and sold shares of the company. Confluence Wealth Services Inc. purchased a new stake in shares of MongoDB during the fourth quarter worth $25,000. Bank of New Hampshire purchased a new stake in shares of MongoDB during the first quarter worth $25,000. Arlington Partners LLC purchased a new stake in shares of MongoDB during the fourth quarter worth $30,000. HBC Financial Services PLLC increased its position in shares of MongoDB by 3,233.3% during the fourth quarter. HBC Financial Services PLLC now owns 400 shares of the company’s stock worth $39,000 after acquiring an additional 388 shares during the period. Finally, Covestor Ltd purchased a new position in MongoDB in the fourth quarter valued at $43,000. 88.70% of the stock is currently owned by institutional investors and hedge funds.

About MongoDB (Get Rating)

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.

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Dropbox Unplugs Data Center to Test Resilience

MMS Founder
MMS Matt Saunders

Article originally posted on InfoQ. Visit InfoQ

Dropbox have published a detailed account of why and how they unplugged an entire data center to test their disaster readiness. With a dependency on their San Jose data center, Dropbox ran a multi-year project to engineer away this single point of failure in their metadata stack, culminating in a deliberate and successful switch-off of the San Jose data center.

Dropbox had moved away from AWS for storing data, but were still heavily centralised and dependent on their San Jose data center. The recovery time from an outage at San Jose was considered to be far in excess of what was desired – hence initiating a project to improve this in case of a significant disaster – such as an earthquake at the nearby San Andreas Fault. The improvement was measured as a Recovery Time Objective (RTO) – a standard measure from Disaster Recovery Planning (DRP) for the maximum time a system can be tolerably down for after a failure or disaster occurs.

The overall architecture of Dropbox’s systems involves a system to store files (block storage), and another system to store the metadata about those files. The architecture for block storage – named Magic Pocket – allows block data to be served from multiple data centers in an active/active configuration, and part of this new resilience work involved making the metadata service more resilient, and eventually also active/active too. Making the metadata stack resilient proved to be a difficult goal to achieve. Some earlier design tradeoffs – such as using asynchronous replication of MySQL data between regions and using caches to scale databases – forced a rethink of the disaster readiness plan.

The disaster readiness team began building tools to make performing frequent failovers possible, and ran their first formalized failover in 2019. Following this, quarterly failovers were performed, until a fault in the failover tooling caused a 47 minute outage in May 2020, highlighting that the failover tooling did not itself fail safely. A dedicated Disaster Readiness (DR) team was formed, also charged with owning all failover process and tooling, and performing regular failovers, thus removing the competing priorities involved before there was a dedicated team.

Early 2020 brought a new evolution of the failover tooling – with a runbook made up of a number of failover tasks linked together in a DAG (directed acyclic graph). This made for a much more lightweight failover process, with re-usable tasks and easier regular testing of each task. Also, it became easy to see whether tasks had succeeded or not, and important actions were guarded in case of a failure in a preceding task.

Directed Acyclic Graph

Dropbox implemented other changes to help reduce risk, with a customer-first strategy:

  •  Routine testing of key failover procedures – regular automated small-scale tests of failover tasks
  •  Improved operational procedures – a formalized go/no-go decision point, checks leading up to a failover “countdown”, and clearly defined roles for people during a failover
  •  Abort criteria and procedures – clearly defining when and how a failover would be aborted

In addition to working on the DR processes and tools as described above, a small team also began working on true active/passive architecture. This involved improving internal services that were still running only in the San Jose data center, so that they could either run multi-homed in multiple data centers, or single-homed in a location other than San Jose. Techniques and tools used here included using the load-balancer Envoy, and using common failover RPC clients with Courier to redirect a service’s client requests to another data center.
 
The final steps in preparation for unplugging San Jose involved making a detailed Method of Procedure (MoP) to perform the failover, and this was tested on a lower-risk data center first – that at Dallas Fort Worth. After disconnecting one of the DFW data centers, whilst performing validations that everything was still working, engineers realised that external availability was dropping, and the failover was aborted four minutes later. This test had revealed a previously hidden single point-of-failure in an S3 proxy service.
 
The failed test provided several lessons to the team – significantly that blackhole tests needed to test entire regions (metros) and not individual data centers. A second test at DFW after adjusting the MoP to accommodate these learnings was successful. Finally, the team were ready to disconnect the San Jose data center. Thanks to all the planning, the new tooling and procedures, there was no impact to global availability, and the anti-climactic event was declared a success. This provided a significantly reduced RTO and proved that Dropbox could run indefinitely from another region, and without San Jose.
 
The key takeaways from this multi-year project were that it takes training and practice to get stronger at Disaster Readiness. Dropbox now have the ability to conduct blackhole exercises regularly, and this ensures that the DR capabilities will only continue to improve, with users never noticing when something goes wrong.

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Applying Observability to Increase Delivery Speed and Flow in Teams

MMS Founder
MMS Ben Linders

Article originally posted on InfoQ. Visit InfoQ

When we design team and departmental processes, we want to know what’s happening in the software teams. Asking team members to provide information or fill in fields in tools adds a burden and distorts reality. Setting up observability in the software can provide alternative insights in a less intrusive way. Observability in the software can be an asset to organizing teams.

Jessica Kerr spoke about applying observability for speed and flow of delivery at QCon London 2022 and QCon Plus May 2022.

When you want to go fast, it helps to see where you’re going, Kerr stated. To deliver fast and focus on flow, teams can use observability, as Kerr explained:

Observability gives developers clues into the consequences of each change they make: did it do what we expected? Did it do anything else harmful?

Observability lets developers see performance regressions and error rates, check usage on features, and show the functionality to others in an intelligible, referenceable way, Kerr said.

Kerr explained how observability in the software can become an asset to organizing teams:

As leaders of teams, we can use observability by adding tracing to continuous integration. Then we can measure deploy frequency and build times. We can graph those the same way we measure performance in software. And when it’s time to improve lead time (from commit to production), we can see what’s taking so long in our builds and fix it.

A little bit of system knowledge plus a distributed trace gives a lot of insight, Kerr concluded.

InfoQ interviewed Jessica Kerr about how observability can be applied to increase the speed and flow of delivery.

InfoQ: How can building in observability help to see performance and cost impacts?

Jessica Kerr: When Honeycomb added the ability to store our customers’ event data for up to 60 days, instead of only what fits in local storage, lots of consequences happened. Queries over a wide range of data took minutes instead of seconds — even tens of minutes. Querying our traces, we could see exactly how much. Looking at a trace, we could see why: hundreds of fetches to S3 bogged down our database servers.

To fix this, we moved those fetches to AWS lambda functions (I gave a talk at StrangeLoop 2020 on how we used serverless to speed up our servers). This lets us scale our compute power with the scope of the query, live on demand. It also scales our AWS costs rather unpredictably. To help with this, we built observability into our lambda functions, so we can see exactly which queries (and whose queries) are costing us a lot. We got in touch with some customers to help them use Honeycomb more efficiently.

And then! when AWS released Graviton 2 for Lambda—it’s a different computer architecture, cheaper and supposedly faster—we tried it out. We easily measured the difference. At first it was less predictable and slower, so we scaled back our use of it until we made our function more compatible.

Serverless is particularly inscrutable without observability. With it, we can measure the cost of each operation, such as this database query.

InfoQ: How can developers benefit from adding observability to their software?

Kerr: Let me give an example. In one of my personal toy applications, I started with traces instead of logs. As soon as I looked at one, I found a concurrency error. That would have been really hard to find any other way, because the waterfall view of the distributed trace clearly showed an overlap where I knew there shouldn’t be one.

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