DBMS > Badger vs. Datomic vs. Realm vs. Teradata Aster

System Properties Comparison Badger vs. Datomic vs. Realm vs. Teradata Aster

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Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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 DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Platform for big data analytics on multistructured data sources and types

Primary database model

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Website

github.com/dgraph-io/badger

www.datomic.com

realm.io

Technical documentation

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

docs.datomic.com

realm.io/docs

Developer

DGraph Labs

Cognitect

Realm, acquired by MongoDB in May 2019

Teradata

Initial release

2017

2012

2014

2005

Current release

1.0.7075, December 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

limited edition free

Open Source

commercial

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, Clojure

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Android
Backend: server-less
iOS
Windows

Linux

Data scheme

schema-free

yes

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

defined schema within the relational store; partial schema or schema free in the Aster File Store

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.

yes

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Clojure
Java

.Net
Java

with Android only
Objective-C
React Native
Swift

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

Transaction Functions

runs within the applications so server-side scripts are unnecessary

R packages

Triggers

By using transaction functions

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

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

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

In-Memory realm

User concepts

Access control

yes

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
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