Timescale is leading the next wave of NYC database tech

Data is the lifeblood of the modern corporation, yet acquiring, storing, processing, and analyzing it remains a remarkably challenging and expensive project. Every time data infrastructure finally catches up with the streams of information pouring in, another source and more demanding decision-making makes the existing technology obsolete.

Few cities rely on data the same way as New York City, nor has any other city so shaped the technology that underpins our data infrastructure. Back in the 1960s, banks and accounting firms helped to drive much of the original computation industry with their massive finance applications. Today, that industry has been supplanted by finance and advertising, both of which need to make microsecond decisions based on petabyte datasets and complex statistical models.

Unsurprisingly, the city’s hunger for data has led to waves of database companies finding their home in the city.

As web applications became increasingly popular in the mid-aughts, SQL databases came under increasing strain to scale, while also proving to be inflexible in terms of their data schemas for the fast-moving startups they served. That problem spawned Manhattan-based MongoDB, whose flexible “NoSQL” schemas and horizontal scaling capabilities made it the default choice for a generation of startups. The company would go on to raise $311 million according to Crunchbase, and debuted late last year on NASDAQ, trading today with a market cap of $2 billion.

At the same time that the NoSQL movement was hitting its stride, academic researchers and entrepreneurs were exploring how to evolve SQL to scale like its NoSQL competitors, while retaining the kinds of features (joining tables, transactions) that make SQL so convenient for developers.

One leading company in this next generation of database tech is New York-based Cockroach Labs, which was founded in 2015 by a trio of former Square, Viewfinder, and Google engineers. The company has gone on to raise more than $50 million according to Crunchbase from a luminary list of investors including Peter Fenton at Benchmark, Mike Volpi at Index, and Satish Dharmaraj at Redpoint, along with GV and Sequoia.

While web applications have their own peculiar data needs, the rise of the internet of things (IoT) created a whole new set of data challenges. How can streams of data from potentially millions of devices be stored in an easily analyzable manner? How could companies build real-time systems to respond to that data?

Mike Freedman and Ajay Kulkarni saw that problem increasingly manifesting itself in 2015. The two had been roommates at MIT in the late 90s, and then went on separate paths into academia and industry respectively. Freedman went to Stanford for a PhD in computer science, and nearly joined the spinout of Nicira, which sold to VMware in 2012 for $1.26 billion. Kulkarni joked that “Mike made the financially wise decision of not joining them,” and Freedman eventually went to Princeton as an assistant professor, and was awarded tenure in 2013. Kulkarni founded and worked at a variety of startups including GroupMe, as well as receiving an MBA from MIT.

The two had startup dreams, and tried building an IoT platform. As they started building it though, they realized they would need a real-time database to process the data streams coming in from devices. “There are a lot of time series databases, [so] let’s grab one off the shelf, and then we evaluated a few,” Kulkarni explained. They realized what they needed was a hybrid of SQL and NoSQL, and nothing they could find offered the feature set they required to power their platform. That challenge became the problem to be solved, and Timescale was born.

In many ways, Timescale is how you build a database in 2018. Rather than starting de novo, the team decided to build on top of Postgres, a popular open-source SQL database. “By building on top of Postgres, we became the more reliable option,” Kulkarni said of their thinking. In addition, the company opted to make the database fully open source. “In this day and age, in order to get wide adoption, you have to be an open source database company,” he said.

Since the project’s first public git commit on October 18, 2016, the company’s database has received nearly 4,500 stars on Github, and it has raised $16.1 million from Benchmark and NEA .

Far more important though are their customers, who are definitely not the typical tech startup roster and include companies from oil and gas, mining, and telecommunications. “You don’t think of them as early adopters, but they have a need, and because we built it on top of Postgres, it integrates into an ecosystem that they know,” Freedman explained. Kulkarni continued, “And the problem they have is that they have all of this time series data, and it isn’t sitting in the corner, it is integrated with their core service.”

New York has been a strong home for the two founders. Freedman continues to be a professor at Princeton, where he has built a pipeline of potential grads for the company. More widely, Kulkarni said, “Some of the most experienced people in databases are in the financial industry, and that’s here.” That’s evident in one of their investors, hedge fund Two Sigma. “Two Sigma had been the only venture firm that we talked to that already had built out their own time series database,” Kulkarni noted.

The two also benefit from paying customers. “I think the Bay Area is great for open source adoption, but a lot of Bay Area companies, they develop their own database tech, or they use an open source project and never pay for it,” Kulkarni said. Being in New York has meant closer collaboration with customers, and ultimately more revenues.

Open source plus revenues. It’s the database way, and the next wave of innovation in the NYC enterprise infrastructure ecosystem.


The Final Countdown: Are You Ready for Percona Live 2018?

Are you ready for Percona Live

Are you ready for Percona Live 2018It’s hard to believe Percona Live 2018 starts on Monday! We’re looking forward to seeing everyone in Santa Clara next week! Here are some quick highlights to remember:

  • In addition to all the amazing sessions and keynotes we’ve announced, we’ll be hosting the MySQL Community Awards and the Lightning Talks on Monday during the Opening Reception.
  • We’ve also got a great lineup of demos in the exhibit hall all day Tuesday and Wednesday – be sure to stop by and learn more about open source database products and tools.
  • On Monday, we have a special China Track now available from Alibaba Cloud, PingCAP and Shannon Systems. We’ve just put a $20.00 ticket on sale for that track, and if you have already purchased any of our other tickets, you are also welcome to attend those four sessions.
  • Don’t forget to make your reservation at the Community Dinner. It’s a great opportunity to socialize with everyone and Pythian is always a wonderful host!

Thanks to everyone who is sponsoring, presenting and attending! The community is who makes this event successful and so much fun to be a part of!

The post The Final Countdown: Are You Ready for Percona Live 2018? appeared first on Percona Database Performance Blog.


Percona Toolkit 3.0.9 Is Now Available

Percona Toolkit 3.0.9Percona announces the release of Percona Toolkit 3.0.9 on April 20, 2018.

Percona Toolkit is a collection of advanced open source command-line tools, developed and used by the Percona technical staff, that are engineered to perform a variety of MySQL®, MongoDB® and system tasks that are too difficult or complex to perform manually. With over 1,000,000 downloads, Percona Toolkit supports Percona Server for MySQL, MySQL, MariaDB®, Percona Server for MongoDB and MongoDB.

Percona Toolkit, like all Percona software, is free and open source. You can download packages from the website or install from official repositories.

This release includes the following changes:

New Tools:

  • PT-1501: pt-secure-collect – new tool to collect and sanitize pt-tools outputs

New Features:

  • PT-1530: Add support for encryption status to pt-mysql-summary
  • PT-1526: Add ndb status to pt-mysql-summary (Thanks Fernando Ipar)
  • PT-1525: Add support for MySQL 8 roles into pt-mysql-summary
  • PT-1509: Make pt-table-sync only set binlog_format when necessary (Thanks Moritz Lenz)
  • PT-1508: Add --read-only-interval and --fail-successive-errors flags to pt-heartbeat (Thanks Shlomi Noach)
  • PT-243: Add --max-hostname-length and --max-line-length flags to pt-query-digest

Bug Fixes:

  • PT-1527: Fixed pt-table-checksum ignores --nocheck-binlog-format


  • PT-1507: pt-summary does not reliably read in the transparent huge pages setting (Thanks Nick Veenhof)
  • PT-1488: pt-show-grants support for MySQL 8.0

Help us improve our software quality by reporting any bugs you encounter using our bug tracking system.

The post Percona Toolkit 3.0.9 Is Now Available appeared first on Percona Database Performance Blog.


Percona Monitoring and Management (PMM) 1.10.0 Is Now Available

Percona Monitoring and Management

Percona Monitoring and Management (PMM) is a free and open-source platform for managing and monitoring MySQL® and MongoDB® performance. You can run PMM in your own environment for maximum security and reliability. It provides thorough time-based analysis for MySQL® and MongoDB® servers to ensure that your data works as efficiently as possible.

Percona Monitoring and ManagementWe focused mainly on two features in 1.10.0, but there are also several notable improvements worth highlighting:

  • Annotations – Record and display Application Events as Annotations using pmm-admin annotate
  • Grafana 5.0 – Improved visualization effects
  • Switching between Dashboards – Restored functionality to preserve host when switching dashboards
  • New Percona XtraDB Cluster Overview graphs – Added Galera Replication Latency graphs on Percona XtraDB Cluster Overview dashboard with consistent colors

The issues in the release include four new features & improvements, and eight bugs fixed.


Application events are one of the contributors to changes in database performance characteristics, and in this release PMM now supports receiving events and displaying them as Annotations using the new command pmm-admin annotate. A recent Percona survey reveals that Database and DevOps Engineers highly value visibility into the Application layer.  By displaying Application Events on top of your PMM graphs, Engineers can now correlate Application Events (common cases: Application Deploys, Outages, and Upgrades) against Database and System level metric changes.


For example, you have just completed an Application deployment to version 1.2, which is relevant to UI only, so you want to set tags for the version and interface impacted:

pmm-admin annotate "Application deploy v1.2" --tags "UI, v1.2"

Using the optional --tags allows you to filter which Annotations are displayed on the dashboard via a toggle option.  Read more about Annotations utilization in the Documentation.

Grafana 5.0

We’re extremely pleased to see Grafana ship 5.0 and we were fortunate enough to be at Grafanacon, including Percona’s very own Dimitri Vanoverbeke (Dim0) who presented What we Learned Integrating Grafana and Prometheus!



Included in Grafana 5.0 are a number of dramatic improvements, which in future Percona Monitoring and Management releases we plan to extend our usage of each feature, and the one we like best is the virtually unlimited way you can size and shape graphs.  No longer are you bound by panel constraints to keep all objects at the same fixed height!  This improvement indirectly addresses the visualization error in PMM Server where some graphs would appear to be on two lines and ended up wasting screen space.

Switching between Dashboards

PMM now allows you to navigate between dashboards while maintaining the same host under observation, so that for example you can start on MySQL Overview looking at host serverA, switch to MySQL InnoDB Advanced dashboard and continue looking at serverA, thus saving you a few clicks in the interface.

New Percona XtraDB Cluster Galera Replication Latency Graphs

We have added new Percona XtraDB Cluster Replication Latency graphs on our Percona XtraDB Cluster Galera Cluster Overview dashboard so that you can compare latency across all members in a cluster in one view.

Issues in this release

New Features & Improvements

  • PMM-2330Application Annotations DOC Update
  • PMM-2332Grafana 5 DOC Update
  • PMM-2293Add Galera Replication Latency Graph to Dashboard PXC/Galera Cluster Overview RC Ready
  • PMM-2295Improve color selection on Dashboard PXC/Galera Cluster Overview RC Ready

Bugs fixed

  • PMM-2311Fix misalignment in Query Analytics Metrics table RC Ready
  • PMM-2341Typo in text on password page of OVF RC Ready
  • PMM-2359Trim leading and trailing whitespaces for all fields on AWS/OVF Installation wizard RC Ready
  • PMM-2360Include a “What’s new?” link for Update widget RC Ready
  • PMM-2346Arithmetic on InnoDB AHI Graphs are invalid DOC Update
  • PMM-2364QPS are wrong in QAN RC Ready
  • PMM-2388Query Analytics does not render fingerprint section in some cases DOC Update
  • PMM-2371Pass host when switching between Dashboards

How to get PMM

PMM is available for installation using three methods:

Help us improve our software quality by reporting any Percona Monitoring and Management bugs you encounter using our bug tracking system.

The post Percona Monitoring and Management (PMM) 1.10.0 Is Now Available appeared first on Percona Database Performance Blog.


Restore a MongoDB Logical Backup

MongoDB Logical Backup

MongoDB Logical BackupIn this article, we will explain how to restore a MongoDB logical backup performed via ‘mongodump’ to a mongod instance.

MongoDB logical backup requires the use of the ‘mongorestore‘ tool to perform the restore backup. This article focuses on this tool and process.

Note: Percona develops a backup tool named Percona-Lab/mongodb-consistent-backup, which is a wrapper for ‘mongodump‘, adding cluster-wide backup consistency. The backups created by mongodb_consistent_backup (in Dump/Mongodump mode) can be restored using the exact same steps as a regular ‘mongodump’ backup – no special steps!

Mongorestore Command Flags

–host/–port (and –user/–password)

Required, even if you’re using the default host/port (localhost:27017). If authorization is enabled, add –user/–password flags also.


This is almost always required. This causes ‘mongodump‘ to drop the collection that is being restored before restoring it. Without this flag, the documents from the backup are inserted one at a time and if they already exist the restore fails.


This is almost always required. Replays the oplog that was dumped by mongodump. It is best to include this flag on replset-based backups unless there is a specific reason not to. You can tell if the backup was from a replset by looking for the file ‘oplog.bson‘ at the base of the dump directory.


Required. The path to the mongodump data.


Optional. For mongodump >= 3.2, enables inline compression on the restore. This is required if ‘mongodump‘ used the –gzip flag (look for *.bson.gz files if you’re not sure if the collection files have no .gz suffix, don’t use –gzip).


Optional. For mongodump >= 3.2 only, sets the number of collections to insert in parallel. By default four threads are used, and if you have a large server and you want to restore faster (more resource usage though), you could increase this number. Note that each thread uncompresses bson if the ‘–gzip‘ flag is used, so consider this when raising this number.


  1. (Optional) If the backup is archived (mongodb_consistent_backup defaults to creating tar archives), un-archive the backup so that ‘mongorestore‘ can access the .bson/.bson.gz files:
    $ tar -C /opt/mongodb/backup/testbackup/20160809_1306 -xvf /opt/mongodb/backup/testbackup/20160809_1306/test1.tar

    ** This command un-tars the backup to ‘/opt/mongodb/backup/testbackup/20160809_1306/test1/dump’ **

  2. Check (and then check again!) that you’re restoring the right backup to the right host. When in doubt, it is safer to ask the customer or others.
    1. The Percona ‘mongodb_consistent_backup‘ tool names backup subdirectories by replica set name, so you can ensure you’re restoring the right backup by checking the replica set name of the node you’re restoring to, if it exists.
    2. If you’re restoring to a replica set you will need to restore to the PRIMARY member and there needs to be a majority (so writes are accepted – some exceptions if you override write-concern, but not advised).
  3. Use ‘mongorestore‘ to restore the data by dropping/restoring each collection (–drop flag) and replay the oplog changes (–oplogReplay flag), specifying the restore dir explicitly (–dir flag) to the ‘mongorestore‘ command. In this example I also used authorization (–user/–password flags) and un-compression (–gzip flag):
    $ mongorestore --drop --host localhost --port 27017 --user secret --password secret --oplogReplay --gzip --dir /opt/mongodb/backup/testbackup/20160809_1306/test1/dump
    2016-08-09T14:23:04.057+0200    building a list of dbs and collections to restore from /opt/mongodb/backup/testbackup/20160809_1306/test1/dump dir
    2016-08-09T14:23:04.065+0200    reading metadata for wikipedia.pages from /opt/mongodb/backup/testbackup/20160809_1306/test1/dump/wikipedia/pages.metadata.json.gz
    2016-08-09T14:23:04.067+0200    restoring wikipedia.pages from /opt/mongodb/backup/testbackup/20160809_1306/test1/dump/wikipedia/pages.bson.gz
    2016-08-09T14:23:07.058+0200    [#######.................]  wikipedia.pages  63.9 MB/199.0 MB  (32.1%)
    2016-08-09T14:23:10.058+0200    [###############.........]  wikipedia.pages  127.7 MB/199.0 MB  (64.1%)
    2016-08-09T14:23:13.060+0200    [###################.....]  wikipedia.pages  160.4 MB/199.0 MB  (80.6%)
    2016-08-09T14:23:16.059+0200    [#######################.]  wikipedia.pages  191.5 MB/199.0 MB  (96.2%)
    2016-08-09T14:23:19.071+0200    [########################]  wikipedia.pages  223.5 MB/199.0 MB  (112.3%)
    2016-08-09T14:23:22.062+0200    [########################]  wikipedia.pages  255.6 MB/199.0 MB  (128.4%)
    2016-08-09T14:23:25.067+0200    [########################]  wikipedia.pages  271.4 MB/199.0 MB  (136.4%)
    2016-08-09T14:24:19.058+0200    [########################]  wikipedia.pages  526.9 MB/199.0 MB  (264.7%)
    2016-08-09T14:24:22.058+0200    [########################]  wikipedia.pages  558.9 MB/199.0 MB  (280.8%)
    2016-08-09T14:24:23.521+0200    [########################]  wikipedia.pages  560.6 MB/199.0 MB  (281.6%)
    2016-08-09T14:24:23.522+0200    restoring indexes for collection wikipedia.pages from metadata
    2016-08-09T14:24:23.528+0200    finished restoring wikipedia.pages (32725 documents)
    2016-08-09T14:24:23.528+0200    replaying oplog
    2016-08-09T14:24:23.597+0200    done
    1. If you encounter problems with ‘mongorestore‘, carefully read the error message or rerun with several ‘-v‘ flags, e.g.: ‘-vvv‘. Once you have an error, attempt to troubleshoot the cause.
  4. Check to see that you saw “replaying oplog” and “done” after the restore (last two lines in the example). If you don’t see this, there is a problem.

As you notice, using this tool for MongoDB logical backup is very simple. However, when using sharding please note that –oplog is not available and the mongodump uses the primaries for each shard. As this is not advised typically in production, you might consider looking at Percona-Lab/mongodb-consistent-backup to ensure you are consistent and hitting secondary nodes, like mongodump with replica sets, will work.

If MongoDB and topics like this interest you, please see the document below, we are hiring!

  hiring: true,
  role: "Consultant",
  tech: "MongoDB",
  location: "USA",
  moreInfo: "https://www.percona.com/about-percona/careers/mongodb-consultant-usa-based"

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Webinar Thursday, April 19, 2018: Running MongoDB in Production, Part 1

Running MongoDB

Running MongoDBPlease join Percona’s Senior Technical Operations Architect, Tim Vaillancourt as he presents Running MongoDB in Production, Part 1 on Thursday, April 19, 2018, at 10:00 am PDT (UTC-7) / 1:00 pm EDT (UTC-4).

Are you a seasoned MySQL DBA that needs to add MongoDB to your skills? Are you used to managing a small environment that runs well, but want to know what you might not know yet? This webinar helps you with running MongoDB in production environments.

MongoDB works well, but when it has issues, the number one question is “where should I go to solve a problem?”

This tutorial will cover:

– Logical vs Binary-level backups
– Sharding and Replica-Set Backup strategies
– Filesystem and Network Security
– Operational Security
– External Authentication features of Percona Server for MongoDB
– Securing connections with SSL and MongoDB Authorization
– Encryption at Rest
– New Security features in 3.6
– Monitoring Strategy
– Important metrics to monitor in MongoDB and Linux
– Percona Monitoring and Management

Register for the webinar now.

Part 2 of this series will take place on Thursday, April 26, 2018, at 10:00 am PDT (UTC-7) / 1:00 pm EDT (UTC-4). Register for the second part of this series here.

Running MongoDBTimothy Vaillancourt, Senior Technical Operations Architect

Tim joined Percona in 2016 as Sr. Technical Operations Architect for MongoDB, with the goal to make the operations of MongoDB as smooth as possible. With experience operating infrastructures in industries such as government, online marketing/publishing, SaaS and gaming combined with experience tuning systems from the hard disk all the way up to the end-user, Tim has spent time in nearly every area of the modern IT stack with many lessons learned. Tim is based in Amsterdam, NL and enjoys traveling, coding and music.

Prior to Percona Tim was the Lead MySQL DBA of Electronic Arts’ DICE studios, helping some of the largest games in the world (“Battlefield” series, “Mirrors Edge” series, “Star Wars: Battlefront”) launch and operate smoothly while also leading the automation of MongoDB deployments for EA systems. Before the role of DBA at EA’s DICE studio, Tim served as a subject matter expert in NoSQL databases, queues and search on the Online Operations team at EA SPORTS. Before moving to the gaming industry, Tim served as a Database/Systems Admin operating a large MySQL-based SaaS infrastructure at AbeBooks/Amazon Inc.

The post Webinar Thursday, April 19, 2018: Running MongoDB in Production, Part 1 appeared first on Percona Database Performance Blog.


MongoDB Replica Set Tag Sets

MongoDB Replica Set Tag Sets

MongoDB Replica Set Tag SetsIn this blog post, we will look at MongoDB replica set tag sets, which enable you to use customized write concern and read preferences for replica set members.

This blog post will cover most of the questions that come to mind before using tag sets in a production environment.

  • What scenarios are these helpful for?
  • Do these tag sets work with all read preferences modes?
  • What if we’re already using maxStalenessSeconds along with the read preferences, can we still use a tag set?
  • How can one configure tag sets in a replica set?
  • Do these tags work identically for custom read preferences and write concerns?

Now let’s answer all these questions one by one.

What scenarios are these helpful for?

You can use tags:

  • If replica set members have different configurations and queries need to be redirected to the specific secondaries as per their purpose. For example, production queries can be redirected to the higher configuration member for faster execution and queries used for internal reporting purpose can be redirected to the low configurations secondaries. This will help improve per node resource utilization.
  • When you use custom read preferences, but the reads are routed to a secondary that resides in another data center to make reads more optimized and cost-effective. You can use tag sets to make sure that specific reads are routed to the specific secondary node within the DC.
  • If you want to use custom write concerns with the tag set for acknowledging writes are propagated to the secondary nodes per the requirements.

Do these tag sets work with all read preferences modes?

Yes, these tag-sets work with all the read preferences — except “primary” mode. “Primary” preferred read preference mode doesn’t allow you to add any tag sets while querying.

replicaTest:PRIMARY> db.tagTest.find().readPref('primary', [{"specs" : "low","purpose" : "general"}])
Error: error: {
	"ok" : 0,
	"errmsg" : "Only empty tags are allowed with primary read preference",
	"code" : 2,
	"codeName" : "BadValue"

What if we’re already using maxStalenessSeconds along with the read preferences, can tag set still be used?

Yes, you can use tag sets with a maxStalenessSeconds value. In that case, priority is given to staleness first, then tags, to get the most recent data from the secondary member.

How can one configure tag sets in a replica set?

You can configure tags by adding a parameter in the replica set configuration. Consider this test case with a five members replica set:

"members" : [
			"_id" : 0,
			"name" : "host1:27017",
			"stateStr" : "PRIMARY",
			"_id" : 1,
			"name" : "host2:27017",
			"stateStr" : "SECONDARY",
			"_id" : 2,
			"name" : "host3:27017",
			"stateStr" : "SECONDARY",
			"_id" : 3,
			"name" : "host4:27017",
			"stateStr" : "SECONDARY",
			"_id" : 4,
			"name" : "host5:27017",
			"stateStr" : "SECONDARY",

For our test case, members specification of the host are “specs” and the requirement for the query as per the application is the “purpose,” in order to route queries to specific members in an optimized manner.

You must associate tags to each member by adding it to the replica set configuration:


After adding tags, you can validate these changes by checking replica set configurations like:

	"members" : [
			"_id" : 0,
			"host" : "host1:27017",
			"tags" : {
				"specs" : "high",
				"purpose" : "analytics"
			"_id" : 1,
			"host" : "host2:27017",
			"tags" : {
				"specs" : "high"
			"_id" : 2,
			"host" : "host3:27017",
			"tags" : {
				"specs" : "low",
				"purpose" : "general"
			"_id" : 3,
			"host" : "host4:27017",
			"tags" : {
				"specs" : "high",
				"purpose" : "analytics"
			"_id" : 4,
			"host" : "host5:27017",
			"tags" : {
				"specs" : "low"

Now, we are done with the tag-set configuration.

Do these tags work identically for custom read preferences and write concerns?

No, custom read preferences and write concerns consider tag sets in different ways.

Read preferences routes read operations to a required specific member by following tag values assigned to it, but write concerns follows tag values only to check if the value is unique or not. It will not consider tag values while selecting replica members.

Let us see how to use tag sets with write concerns. As per our test case, we have two unique tag values (i.e., “analytics” and “general”) defined as:

cfg.settings={ getLastErrorModes: {writeNode:{"purpose": 2}}}

You can validate these changes by checking the replica set configuration:

	"settings" : {
			"getLastErrorModes" : {
			"writeNode" : {
				"purpose" : 2

Now let’s try to insert a sample document in the collection named “tagTest” with this write concern:

WriteResult({ "nInserted" : 1 })

Here, the write concern “writeNode” means the client gets a write acknowledgment from two nodes with unique tag set values. If the value set in the configuration exceeds the count of unique values, then it leads to an error at the time of the write:

cfg.settings={ getLastErrorModes: {writeNode:{"purpose": 4}}}
	"nInserted" : 1,
	"writeConcernError" : {
		"code" : 100,
		"codeName" : "CannotSatisfyWriteConcern",
		"errmsg" : "Not enough nodes match write concern mode "writeNode""

You can perform read and write operations with tag sets like this:


I hope this helps you to understand how to configure MongoDB replica set tag sets, how the read preferences and write concerns handle them, and where you can use them

The post MongoDB Replica Set Tag Sets appeared first on Percona Database Performance Blog.


This Week in Data with Colin Charles 35: Percona Live 18 final countdown and a roundup of recent news

Colin Charles

Colin CharlesJoin Percona Chief Evangelist Colin Charles as he covers happenings, gives pointers and provides musings on the open source database community.

Percona Live is just over a week away — there’s an awesome keynote lineup, and you really should register. Also don’t forget to save the date as Percona Live goes to Frankfurt, Germany November 5-7 2018! Prost!

In acquisitions, we have seen MariaDB acquire MammothDB and Idera acquire Webyog.

Some interesting Amazon notes: Amazon Aurora Continues its Torrid Growth, More than Doubling the Number of Active Customers in the Last Year (not sure I’d describe it as torrid but this is great for MySQL and PostgreSQL), comes with a handful of customer mentions. In addition, there have already been 65,000 database migrations on AWS. For context, in late November 2017, it was 40,000 database migrations.


Link List

Upcoming appearances


I look forward to feedback/tips via e-mail at colin.charles@percona.com or on Twitter @bytebot.


The post This Week in Data with Colin Charles 35: Percona Live 18 final countdown and a roundup of recent news appeared first on Percona Database Performance Blog.


Percona Server for MongoDB 3.4.14-2.12 Is Now Available

Percona Server for MongoDB 3.4

Percona Server for MongoDB 3.2Percona announces the release of Percona Server for MongoDB 3.4.14-2.12 on April 12, 2018. Download the latest version from the Percona web site or the Percona Software Repositories.

Percona Server for MongoDB is an enhanced, open source, and highly-scalable database that is a fully-compatible, drop-in replacement for MongoDB 3.4 Community Edition. It supports MongoDB 3.4 protocols and drivers.

Percona Server for MongoDB extends MongoDB Community Edition functionality by including the Percona Memory Engine and MongoRocks storage engine, as well as several enterprise-grade features. It requires no changes to MongoDB applications or code.

This release is based on MongoDB 3.4.14 and does not include any additional changes.

The Percona Server for MongoDB 3.4.14-2.12 release notes are available in the official documentation.

The post Percona Server for MongoDB 3.4.14-2.12 Is Now Available appeared first on Percona Database Performance Blog.


Calling All Polyglots: Percona Live 2018 Keynote Schedule Now Available!

Percona Live 2018 Keynotes

Percona Live 2018 KeynotesWe’ve posted the Percona Live 2018 keynote addresses for the seventh annual Percona Live Open Source Database Conference 2018, taking place April 23-25, 2018 at the Santa Clara Convention Center in Santa Clara, CA. 

This year’s keynotes explore topics ranging from how cloud and open source database adoption accelerates business growth, to leading-edge emerging technologies, to the importance of MySQL 8.0, to the growing popularity of PostgreSQL.

We’re excited by the great lineup of speakers, including our friends at Alibaba Cloud, Grafana, Microsoft, Oracle, Upwork and VividCortex, the innovative leaders on the Cool Technologies panel, and Brendan Gregg from Netflix, who will discuss how to get the most out of your database on a Linux OS, using his experiences at Netflix to highlight examples.  

With the theme of “Championing Open Source Databases,” the conference will feature multiple tracks, including MySQL, MongoDB, Cloud, PostgreSQL, Containers and Automation, Monitoring and Ops, and Database Security. Once again, Percona will be offering a low-cost database 101 track for beginning users who want to learn how to use and operate open source databases.

The Percona Live 2018 keynotes include:

Tuesday, April 24, 2018

  • Open Source for the Modern Business – Peter Zaitsev of Percona will discuss how open source database adoption continues to grow in enterprise organizations, the expectations and definitions of what constitutes success continue to change. A single technology for everything is no longer an option; welcome to the polyglot world. The talk will include several compelling open source projects and trends of interest to the open source database community and will be followed by a round of lightning talks taking a closer look at some of those projects.
  • Cool Technologies Showcase – Four industry leaders will introduce key emerging industry developments. Andy Pavlo of Carnegie Mellon University will discuss the requirements for enabling autonomous database optimizations. Nikolay Samokhvalov of PostgreSQL.org will discuss new PostgreSQL tools. Sugu Sougoumarane of PlanetScale Data will explore how Vitess became a high-performance, scalable and available MySQL clustering cloud solution in line with today’s NewSQL storage systems. Shuhao Wu of Shopify explains how to use Ghostferry as a data migration tool for incompatible cloud platforms.
  • State of the Dolphin 8.0 – Tomas Ulin of Oracle will discuss the focus, strategy, investments and innovations that are evolving MySQL to power next-generation web, mobile, cloud and embedded applications – and why MySQL 8.0 is the most significant MySQL release in its history.
  • Linux Performance 2018 – Brendan Gregg of Netflix will summarize recent performance features to help users get the most out of their Linux systems, whether they are databases or application servers. Topics include the KPTI patches for Meltdown, eBPF for performance observability, Kyber for disk I/O scheduling, BBR for TCP congestion control, and more.

Wednesday, April 25, 2018

  • Panel Discussion: Database Evolution in the Cloud – An expert panel of industry leaders, including Lixun Peng of Alibaba, Sunil Kamath of Microsoft, and Baron Schwartz of VividCortex, will discuss the rapid changes occurring with databases deployed in the cloud and what that means for the future of databases, management and monitoring and the role of the DBA and developer.
  • Future Perfect: The New Shape of the Data Tier – Baron Schwartz of VividCortex will discuss the impact of macro trends such as cloud computing, microservices, containerization, and serverless applications. He will explore where these trends are headed, touching on topics such as whether we are about to see basic administrative tasks become more automated, the role of open source and free software, and whether databases as we know them today are headed for extinction.
  • MongoDB at Upwork – Scott Simpson of Upwork, the largest freelancing website for connecting clients and freelancers, will discuss how MongoDB is used at Upwork, how the company chose the database, and how Percona helps make the company successful.

We will also present the Percona Live 2018 Community Awards and Lightning Talks on Monday, April 23, 2018, during the Opening Night Reception. Don’t miss the first day of tutorials and Opening Night Reception!

Register for the conference on the Percona Live Open Source Database Conference 2018 website.


Limited Sponsorship opportunities for Percona Live 2018 Open Source Database Conference are still available, and offer the opportunity to interact with the DBAs, sysadmins, developers, CTOs, CEOs, business managers, technology evangelists, solution vendors, and entrepreneurs who typically attend the event. Contact live@percona.com for sponsorship details.

  • Diamond Sponsors – Percona, VividCortex
  • Platinum – Alibaba Cloud, Microsoft
  • Gold Sponsors – Facebook, Grafana
  • Bronze Sponsors – Altinity, BlazingDB, Box, Dynimize, ObjectRocket, Pingcap, Shannon Systems, SolarWinds, TimescaleDB, TwinDB, Yelp
  • Contributing Sponsors – cPanel, Github, Google Cloud, NaviCat
  • Media Sponsors – Database Trends & Applications, Datanami, EnterpriseTech, HPCWire, ODBMS.org, Packt

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