DBMS > Badger vs. CrateDB vs. Galaxybase vs. RocksDB

System Properties Comparison Badger vs. CrateDB vs. Galaxybase vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Distributed Database based on Lucene

Scalable, ACID-compliant native distributed parallel graph platform

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

Primary database model

Key-value store

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Graph DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS

Score	2.84
Rank	#97	Overall
	#16	Key-value stores

Website

github.com/dgraph-io/badger

cratedb.com

galaxybase.com

rocksdb.org

Technical documentation

godoc.org/github.com/dgraph-io/badger

cratedb.com/docs

github.com/facebook/rocksdb/wiki

Developer

DGraph Labs

Crate

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Facebook, Inc.

Initial release

2017

2013

2017

2013

Current release

5.8.1, August 2024

Nov 20, November 2021

9.4.0, June 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

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

Java

C and Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

Strong typed schema

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

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

C++ API
Java API

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

Go
Java
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions (Javascript)

user defined procedures and functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Configurable replication on table/partition-level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

yes

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

rights management via user accounts

Role-based access control

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