TimescaleDB vs InfluxDB

Struggling to choose between TimescaleDB and InfluxDB? 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, InfluxDB is a Development product tagged with time-series, metrics, monitoring.

Its standout features include Time series data storage optimized for IoT sensor data, High availability and horizontal scalability, Built-in data compression, SQL-like query language, Real-time analytics, and it shines with pros like Fast write and query performance, Easy horizontal scaling, Open source with active community, Integrates well with Grafana for visualization.

Feature	TimescaleDB	InfluxDB
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.

InfluxDB

Description: InfluxDB is an open-source time series database optimized for fast, high-availability storage and retrieval of time series data in fields such as operations monitoring, application metrics, Internet of Things sensor data, and real-time analytics. It provides SQL-like query language, data compression, and high throughput.

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

InfluxDB Features

• Time series data storage optimized for IoT sensor data
• High availability and horizontal scalability
• Built-in data compression
• SQL-like query language
• Real-time analytics

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

InfluxDB

Pros

• Fast write and query performance
• Easy horizontal scaling
• Open source with active community
• Integrates well with Grafana for visualization

Cons

• Not suitable for complex queries
• Limited aggregation functions compared to full SQL databases
• No built-in backup utilities
• Less ecosystem support than more established databases

Pricing Comparison

TimescaleDB

• Open Source

InfluxDB

• Open Source
• Subscription-Based