DBMS > Amazon Aurora vs. Axibase vs. CockroachDB vs. GreptimeDB vs. LeanXcale

System Properties Comparison Amazon Aurora vs. Axibase vs. CockroachDB vs. GreptimeDB vs. LeanXcale

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

An open source Time Series DBMS built for increased scalability, high performance and efficiency

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Primary database model

Key-value store
Relational DBMS

Secondary database models

Document store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Website

aws.amazon.com/rds/aurora

axibase.com/docs/atsd/finance

www.cockroachlabs.com

greptime.com

www.leanxcale.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

www.cockroachlabs.com/docs

docs.greptime.com

Developer

Amazon

Axibase Corporation

Cockroach Labs

Greptime Inc.

LeanXcale

Initial release

2015

2013

2015

2022

2015

Current release

15585

23.1.1, May 2023

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache 2.0, commercial license available

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Rust

Server operating systems

hosted

Linux

Linux
macOS
Windows

Android
Docker
FreeBSD
Linux
macOS
Windows

Data scheme

yes

dynamic schema

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes, wire compatible with PostgreSQL

yes

through Apache Derby

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC

gRPC
HTTP API
JDBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Go
Java
PHP
Python
R
Ruby

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

C++
Erlang
Go
Java
JavaScript

C
Java
Scala

Server-side scripts

Stored procedures

yes

Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control

Simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

show all

Recent citations in the news

Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ...
14 May 2024, AWS Blog

Join the preview of Amazon Aurora Limitless Database | Amazon Web Services
27 November 2023, AWS Blog

Improve the performance of generative AI workloads on Amazon Aurora with Optimized Reads and pgvector | Amazon ...
9 February 2024, AWS Blog

New – Amazon Aurora Optimized Reads for Aurora PostgreSQL with up to 8x query latency improvement for I/O ...
8 November 2023, AWS Blog

Knowledge Bases for Amazon Bedrock now supports Amazon Aurora PostgreSQL and Cohere embedding models ...
12 February 2024, AWS Blog

provided by Google News

The Ultimate ATV Test: Suzuki's King Quad 750 AXI Rugged Package vs. Alaska's Hunting Season
20 April 2021, Outdoor Life

provided by Google News

Cockroach Labs Deepens Partnership with Google Cloud, CockroachDB Selected to Join Google Distributed Cloud
9 April 2024, PR Newswire

DoorDash Uses CockroachDB to Create Config Management Platform for Microservices
14 February 2024, InfoQ.com

How to Unlock Real-Time Data Streams with CockroachDB and Amazon MSK | Amazon Web Services
6 November 2023, AWS Blog

CockroachDB tempts legacy databases to crawl into the cloud age
29 January 2024, The Register

How DoorDash Migrated from Aurora Postgres to CockroachDB
5 December 2023, The New Stack

provided by Google News

Share this page