opentsdb: All content tagged as opentsdb in NoSQL databases and polyglot persistence
Thursday, 4 April 2013
Kairosdb - Fast Scalable Time Series Database
kairosdb is introduced as a rewrite of the OpenTSDB written primarily for Cassandra (nb: OpenTSDB was based on HBase). In terms of what it brings new, this page lists:
- Uses Guice to load modules.
- Incorporates Jetty for Rest API and serving up UI.
- Pure Java build tool (Tablesaw)
- UI uses Flot and is client side rendered.
- Ability to customize UI.
- Relative time now includes month and supports leap years.
- Modular data store interface supports:
- HBase
- Cassandra
- H2 (For development)
- Milliseconds data support when using Cassandra.
- Rest API for querying and submitting data.
- Build produces deployable tar, rpm and deb packages.
- Linux start/stop service scripts.
- Faster.
- Made aggregations optional (easier to get raw data).
- Added abilities to import and export data.
- Aggregators can aggregate data for a specified period.
- Aggregators can be stacked or “piped” together.
Source code lives on GitHub. Let’s see where it goes.
Original title and link: Kairosdb - Fast Scalable Time Series Database (©myNoSQL)
Thursday, 22 December 2011
Why We Chose HBase for AppFirst APM
Its performance had a significant impact on our decision making as well. It sustains an enormous number of writes and the read cycle times were much better than we had anticipated. Further, it gives us the option to interact with the Hadoop Ecosystem, including HDFS, Mapreduce, and Zookeeper frameworks. Our enthusiasm for HBase skyrocketed when we discovered how to create map-reduce apps to do a number of management tasks. While Cassandra also has these capabilities, its data model was fundamentally more complex.
What if the whole post would have said: we chose HBase because of
- its seamless integration in the Hadoop ecosystem
- the scalable time series OpenTSDB is built on top of HBase?
Original title and link: Why We Chose HBase for AppFirst APM (©myNoSQL)
via: http://blog.appfirst.com/2011/12/22/why-we-chose-hbase/
Tuesday, 9 November 2010
OpenTSDB: A HBase Scalable Time Series Database
OpenTSDB: a distributed, scalable monitoring system on top of HBase:
Thanks to HBase’s scalability, OpenTSDB allows you to collect many thousands of metrics from thousands of hosts and applications, at a high rate (every few seconds). OpenTSDB will never delete or downsample data and can easily store billions of data points. As a matter of fact, StumbleUpon uses it to keep track of hundred of thousands of time series and collects over 100 million data points per day in their main production cluster.
The source code is available on ☞ GitHub and you can find out more about the project (currently a short intro and a getting started section) ☞ here.
StumbleUpon has built and is using OpenTSDB for the following scenarios:
- Get real-time state information about our infrastructure and services.
- Understand outages or how complex systems interact together.
- Measure SLAs (availability, latency, etc.)
- Tune our applications and databases for maximum performance.
- Do capacity planning.
Original title and link: OpenTSDB: A HBase Scalable Time Series Database (NoSQL databases © myNoSQL)
Thursday, 14 October 2010
OpenTSDB: A Distributed, Scalable Monitoring System on Top of HBase
Tracking this based on Hadoop world in tweets. StumbleUpon plans to open source ☞ OpenTSDB: a scalable time series database built on top of HBase. The project page explains what isOpenTSDB:
OpenTSDB was originally written to address a common need: store and index metrics collected from computer systems (network gear, operating systems, applications) at a large scale, and make this data easily accessible and graphable.
Most existing open-source monitoring systems are not scalable or flexible enough. With OpenTSDB, and thanks to HBase’s scalability, it’s possible to collect many thousands of metrics from thousands of hosts and applications, at a high rate (every few seconds). OpenTSDB will never delete or downsample data and can easily store billions of data points.
Imagine having the ability to quickly generate a graph of the average number of IOPS your databases do, per database schema, over a period of a week, and on the same graph, plot the number of queries per second your servers are handling to see how much of a correlation there is. OpenTSDB makes this type of operation trivial, while manipulating millions of data point for very fine grained, real-time monitoring.
Sounds good. ☞ GitHub repo already set, but nothing in there yet.
Original title and link: OpenTSDB: A Distributed, Scalable Monitoring System on Top of HBase (NoSQL databases © myNoSQL)