DBMS > CockroachDB vs. DataFS vs. Drizzle vs. Heroic

System Properties Comparison CockroachDB vs. DataFS vs. Drizzle vs. Heroic

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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.

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Primary database model

Secondary database models

Graph DBMS

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Website

www.cockroachlabs.com

newdatabase.com

github.com/spotify/heroic

Technical documentation

www.cockroachlabs.com/docs

dev.mobiland.com/Overview.xsp

spotify.github.io/heroic

Developer

Cockroach Labs

Mobiland AG

Drizzle project, originally started by Brian Aker

Spotify

Initial release

2015

2018

2008

2014

Current release

23.1.1, May 2023

1.1.263, October 2022

7.2.4, September 2012

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

Open Source

GNU GPL

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

Server operating systems

Linux
macOS
Windows

Windows

FreeBSD
Linux
OS X

Data scheme

dynamic schema

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

via Elasticsearch

SQL

Support of SQL

yes, wire compatible with PostgreSQL

yes

with proprietary extensions

APIs and other access methods

JDBC

.NET Client API
Proprietary client DLL
WinRT client

JDBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Supported programming languages

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

.Net
C
C#
C++
VB.Net

C
C++
Java
PHP

Server-side scripts

Stored procedures

Triggers

no, except callback-events from server when changes happened

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

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

Proprietary Sharding system

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
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.

User concepts

Access control

Role-based access control

Windows-Profile

Pluggable authentication mechanisms

e.g. LDAP, HTTP

More information provided by the system vendor

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

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

show all

Recent citations in the news

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

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

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

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

provided by Google News

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

Share this page