KairosDB vs Beringei

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

KairosDB is a Ai Tools & Services solution with tags like time-series, database, scalable, java, cassandra.

It boasts features such as Scalable time series data storage, High performance write and query operations, Plugin architecture for custom data processing, Integration with Cassandra for distributed storage, REST API for data access, Aggregation functions for time series data analysis and pros including Highly scalable to handle large time series data, Fast write performance for ingesting high velocity data, Flexible query capabilities, Easy to deploy and manage, Integrates with existing Cassandra clusters, Open source with active development community.

On the other hand, Beringei is a Ai Tools & Services product tagged with time-series, storage, database, analytics.

Its standout features include Stores time series data, Optimized for high volume ingestion and low latency reads, Built for resilience with no single point of failure, Automatically shards data, Compresses data for efficient storage, Exposes data via Thrift API, Supports Cassandra for durable storage, and it shines with pros like Highly scalable and performant, Resilient architecture, Efficient use of storage, Easy to operate at scale, Open source with active development.

Feature	KairosDB	Beringei
Overall Score	N/A	N/A
Primary Category	Ai Tools & Services	Ai Tools & Services

Product Overview

KairosDB

Description: KairosDB is a fast, scalable, open source time series database that is designed to analyze large amounts of time-stamped data. It is written in Java and built on top of Cassandra for high scalability and performance.

Beringei

Description: Beringei is an open-source time series storage engine developed by Facebook. It is optimized for ingesting and serving high-volume time series data with low latencies.

Key Features Comparison

KairosDB Features

• Scalable time series data storage
• High performance write and query operations
• Plugin architecture for custom data processing
• Integration with Cassandra for distributed storage
• REST API for data access
• Aggregation functions for time series data analysis

Beringei Features

• Stores time series data
• Optimized for high volume ingestion and low latency reads
• Built for resilience with no single point of failure
• Automatically shards data
• Compresses data for efficient storage
• Exposes data via Thrift API
• Supports Cassandra for durable storage

Pros & Cons Analysis

KairosDB

Pros

• Highly scalable to handle large time series data
• Fast write performance for ingesting high velocity data
• Flexible query capabilities
• Easy to deploy and manage
• Integrates with existing Cassandra clusters
• Open source with active development community

Cons

• Limited ad-hoc analytics compared to full analytics databases
• Less ecosystem support than more established databases
• Requires expertise with Cassandra for production deployments
• Not ideal for complex time series modeling

Beringei

Pros

• Highly scalable and performant
• Resilient architecture
• Efficient use of storage
• Easy to operate at scale
• Open source with active development

Cons

• Complex installation and configuration
• Requires expertise to tune and operate
• Limited to time series data only
• Less flexible query capabilities than SQL databases

Pricing Comparison

KairosDB

• Open Source

Beringei

• Open Source