DBMS > Altibase vs. Badger vs. Datomic vs. OrigoDB

System Properties Comparison Altibase vs. Badger vs. Datomic vs. OrigoDB

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

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

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

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Document store
Object oriented DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

altibase.com

github.com/dgraph-io/badger

www.datomic.com

origodb.com

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

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

docs.datomic.com

origodb.com/docs

Developer

Altibase

DGraph Labs

Cognitect

Robert Friberg et al

Initial release

1999

2017

2012

2009

under the name LiveDB

Current release

v7.3, 2023, August 2023

1.0.6735, June 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache 2.0

commercial

limited edition free

Open Source

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, Clojure

Server operating systems

AIX
HP-UX
Linux

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL-92

APIs and other access methods

JDBC
ODBC
Proprietary protocol

RESTful HTTP API

.NET Client API
HTTP API
LINQ

Supported programming languages

C
C++
Java

Clojure
Java

.Net

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

Transaction Functions

yes

Triggers

yes

By using transaction functions

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

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

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

yes

Write ahead log

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

Role based authorization

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