TimescaleDB vs OpenTSDB

Struggling to choose between TimescaleDB and OpenTSDB? Both products offer unique advantages, making it a tough decision.

TimescaleDB is a Databases solution with tags like timeseries, postgresql, sql, timeseries, opensource.

It boasts features such as Designed for time-series data, Scales to handle high volumes of time-series data, SQL compliant and works with existing PostgreSQL tools, Advanced compression algorithms, Support for complex queries across large datasets, Data partitioning for optimized query performance, Native support for time-series analytics functions, High availability with streaming replication and automated failover and pros including Significantly improves performance for time-series workloads, Leverages the power and ecosystem of PostgreSQL, Open source and community supported, Flexible deployment options including on-prem or in the cloud, Cost effective compared to other time-series databases.

On the other hand, OpenTSDB is a Development product tagged with time-series, monitoring, analytics.

Its standout features include Distributed and horizontally scalable architecture, Built on top of HBase for reliability and scalability, Customizable rollup tables for aggregating data, Tag-based metric model for organizing time series data, HTTP API for writing and querying data, Support for downsampling and aggregation of data, Plugin architecture for adding functionality, and it shines with pros like Handles massive amounts of time series data, Low latency queries, Easy to scale horizontally, Integrates well with Hadoop ecosystem, Open source and free to use.

To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.

TimescaleDB

TimescaleDB

TimescaleDB is an open-source time-series database optimized for fast ingest and complex queries. It is engineered up from PostgreSQL, enabling scalability and SQL queries.

Categories:
timeseries postgresql sql timeseries opensource

TimescaleDB Features

  1. Designed for time-series data
  2. Scales to handle high volumes of time-series data
  3. SQL compliant and works with existing PostgreSQL tools
  4. Advanced compression algorithms
  5. Support for complex queries across large datasets
  6. Data partitioning for optimized query performance
  7. Native support for time-series analytics functions
  8. High availability with streaming replication and automated failover

Pricing

  • Open Source

Pros

Significantly improves performance for time-series workloads

Leverages the power and ecosystem of PostgreSQL

Open source and community supported

Flexible deployment options including on-prem or in the cloud

Cost effective compared to other time-series databases

Cons

Less flexible than a pure JSON document store

Not ideal for non time-series data

Advanced tuning required for optimal performance

Limited options for commercial support


OpenTSDB

OpenTSDB

OpenTSDB is a distributed, scalable time series database optimized for storing and serving massive amounts of time series data without losing granularity. It's designed to be used as a backend for monitoring systems and analytics platforms.

Categories:
time-series monitoring analytics

OpenTSDB Features

  1. Distributed and horizontally scalable architecture
  2. Built on top of HBase for reliability and scalability
  3. Customizable rollup tables for aggregating data
  4. Tag-based metric model for organizing time series data
  5. HTTP API for writing and querying data
  6. Support for downsampling and aggregation of data
  7. Plugin architecture for adding functionality

Pricing

  • Open Source

Pros

Handles massive amounts of time series data

Low latency queries

Easy to scale horizontally

Integrates well with Hadoop ecosystem

Open source and free to use

Cons

Limited ad-hoc querying capabilities

Steep learning curve

Not optimized for real-time streaming data

No built-in visualization or dashboarding