DBMS > Bangdb vs. Datomic vs. Realm vs. RocksDB vs. Teradata Aster

System Properties Comparison Bangdb vs. Datomic vs. Realm vs. RocksDB vs. Teradata Aster

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

Converged and high performance database for device data, events, time series, document and graph

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

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

Platform for big data analytics on multistructured data sources and types

Primary database model

Document store
Graph DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

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

Website

Technical documentation

docs.bangdb.com

docs.datomic.com

realm.io/docs

github.com/facebook/rocksdb/wiki

Developer

Sachin Sinha, BangDB

Cognitect

Realm, acquired by MongoDB in May 2019

Facebook, Inc.

Teradata

Initial release

2012

2014

2013

2005

Current release

BangDB 2.0, October 2021

1.0.6735, June 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

BSD 3

commercial

limited edition free

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Java, Clojure

C++

Server operating systems

Linux

All OS with a Java VM

Android
Backend: server-less
iOS
Windows

Linux

Data scheme

schema-free

yes

schema-free

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: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP API

C++ API
Java API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Java
Python

Clojure
Java

.Net
Java

with Android only
Objective-C
React Native
Swift

C
C++
Go
Java
Perl
Python
Ruby

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

yes, Notifications (with Streaming only)

By using transaction functions

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

But extensive use of caching in the application peers

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

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

Tunable consistency, set CAP knob accordingly

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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, run db with in-memory only mode

yes

recommended only for testing and development

yes

In-Memory realm

yes

User concepts

Access control

yes (enterprise version only)

yes

fine grained access rights according to SQL-standard

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