DBMS > Bangdb vs. Datomic vs. Oracle NoSQL vs. RethinkDB

System Properties Comparison Bangdb vs. Datomic vs. Oracle NoSQL vs. RethinkDB

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Editorial information provided by DB-Engines

Name

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 multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

Document store

Secondary database models

Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Website

bangdb.com

www.datomic.com

www.oracle.com/database/nosql/technologies/nosql

rethinkdb.com

Technical documentation

docs.bangdb.com

docs.datomic.com

docs.oracle.com/en/database/other-databases/nosql-database/index.html

rethinkdb.com/docs

Developer

Sachin Sinha, BangDB

Cognitect

Oracle

The Linux Foundation

since July 2017

Initial release

2012

2011

2009

Current release

BangDB 2.0, October 2021

1.0.6735, June 2023

23.3, December 2023

2.4.1, August 2020

License

Commercial or Open Source

Open Source

BSD 3

commercial

limited edition free

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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++

Java, Clojure

Java

C++

Server operating systems

Linux

All OS with a Java VM

Linux
Solaris SPARC/x86

Linux
OS X
Windows

Data scheme

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

Typing

predefined data types such as float or date

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

yes

optional

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like DML and DDL statements

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP API

Supported programming languages

C
C#
C++
Java
Python

Clojure
Java

C
C#
Go
Java
JavaScript (Node.js)
Python

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

yes

Transaction Functions

Triggers

yes, Notifications (with Streaming only)

By using transaction functions

Client-side triggers through changefeeds

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

Sharding

range based

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

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

MVCC based

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

off heap cache

User concepts

Access control

yes (enterprise version only)

Access rights for users and roles

yes

users and table-level permissions

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