DBMS > CockroachDB vs. Geode vs. KeyDB vs. VoltDB

System Properties Comparison CockroachDB vs. Geode vs. KeyDB vs. VoltDB

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Editorial information provided by DB-Engines

Name

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.

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Key-value store

Relational DBMS

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

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

www.cockroachlabs.com

geode.apache.org

github.com/Snapchat/KeyDB
keydb.dev

www.voltdb.com

Technical documentation

www.cockroachlabs.com/docs

geode.apache.org/docs

docs.keydb.dev

docs.voltdb.com

Developer

Cockroach Labs

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

EQ Alpha Technology Ltd.

VoltDB Inc.

Initial release

2015

2002

2019

2010

Current release

24.1.0, May 2024

1.1, February 2017

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

BSD-3

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java

C++

Java, C++

Server operating systems

Linux
macOS
Windows

All OS with a Java VM

the JDK (8 or later) is also required

Linux

Linux
OS X

for development

Data scheme

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

SQL-like query language (OQL)

yes

only a subset of SQL 99

APIs and other access methods

JDBC

Java Client API
Memcached protocol
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protoco

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

.Net
All JVM based languages
C++
Groovy
Java
Scala

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Lua

Java

Triggers

yes

Cache Event Listeners

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

yes, on a single node

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

Role-based access control

Access rights per client and object definable

simple password-based access control and ACL

Users and roles with access to stored procedures

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