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.

Feature	TimescaleDB	OpenTSDB
Overall Score	N/A	N/A
Primary Category	Databases	Development

Product Overview

TimescaleDB

Description: 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.

OpenTSDB

Description: 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.

Key Features Comparison

TimescaleDB Features

• 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

OpenTSDB Features

• 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

Pros & Cons Analysis

TimescaleDB

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

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

Pricing Comparison

TimescaleDB

• Open Source

OpenTSDB

• Open Source