DBMS > CockroachDB vs. etcd vs. HarperDB vs. Percona Server for MongoDB vs. RocksDB

System Properties Comparison CockroachDB vs. etcd vs. HarperDB vs. Percona Server for MongoDB vs. RocksDB

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.

A distributed reliable key-value store

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

www.cockroachlabs.com

etcd.io
github.com/etcd-io/etcd

www.harperdb.io

www.percona.com/mongodb/software/percona-server-for-mongodb

rocksdb.org

Technical documentation

www.cockroachlabs.com/docs

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

docs.harperdb.io/docs

docs.percona.com/percona-distribution-for-mongodb

github.com/facebook/rocksdb/wiki

Developer

Cockroach Labs

HarperDB

Percona

Facebook, Inc.

Initial release

2015

2017

2015

2013

Current release

23.1.1, May 2023

3.4, August 2019

3.1, August 2021

3.4.10-2.10, November 2017

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

Open Source

Apache Version 2.0

commercial

free community edition available

Open Source

GPL Version 2

Open Source

BSD

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

Node.js

C++

Server operating systems

Linux
macOS
Windows

FreeBSD
Linux
Windows

experimental

Linux
OS X

Linux

Data scheme

dynamic schema

schema-free

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

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

SQL

Support of SQL

yes, wire compatible with PostgreSQL

SQL-like data manipulation statements

APIs and other access methods

JDBC

gRPC
JSON over HTTP

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

proprietary protocol using JSON

C++ API
Java API

Supported programming languages

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

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

JavaScript

Triggers

yes, watching key changes

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

A table resides as a whole on one (or more) nodes in a cluster

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes

the nodes on which a table resides can be defined

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Atomic execution of specific operations

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

In-memory capabilities

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

yes

via In-Memory Engine

yes

User concepts

Access control

Role-based access control

Access rights for users and roles

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