DBMS > Badger vs. Brytlyt vs. Datomic vs. IBM Db2 Event Store vs. RethinkDB

System Properties Comparison Badger vs. Brytlyt vs. Datomic vs. IBM Db2 Event Store vs. RethinkDB

Editorial information provided by DB-Engines

Name

Description

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

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Distributed Event Store optimized for Internet of Things use cases

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Key-value store

Relational DBMS

Event Store
Time Series DBMS

Document store

Secondary database models

Spatial DBMS

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

Score	0.20
Rank	#325	Overall
	#49	Key-value stores

Score	0.38
Rank	#279	Overall
	#126	Relational DBMS

Score	1.76
Rank	#145	Overall
	#66	Relational DBMS

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	2.84
Rank	#106	Overall
	#19	Document stores

Website

github.com/dgraph-io/badger

brytlyt.io

www.datomic.com

www.ibm.com/products/db2-event-store

rethinkdb.com

Technical documentation

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

docs.brytlyt.io

docs.datomic.com

www.ibm.com/docs/en/db2-event-store

rethinkdb.com/docs

Developer

DGraph Labs

Brytlyt

Cognitect

IBM

The Linux Foundation

since July 2017

Initial release

2017

2016

2012

2017

2009

Current release

5.0, August 2023

1.0.6735, June 2023

2.0

2.4.1, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

limited edition free

commercial

free developer edition available

Open Source

Apache Version 2

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, C++ and CUDA

Java, Clojure

C and C++

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

All OS with a Java VM

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Clojure
Java

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

Transaction Functions

yes

Triggers

yes

By using transaction functions

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

But extensive use of caching in the application peers

Active-active shard replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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 single-document operations

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

MVCC based

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

users and table-level permissions

More information provided by the system vendor

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More resources

DB-Engines blog posts

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