DBMS > Bangdb vs. BigObject vs. Datomic vs. NSDb vs. RethinkDB

System Properties Comparison Bangdb vs. BigObject vs. Datomic vs. NSDb vs. RethinkDB

Editorial information provided by DB-Engines

Name

Description

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

Analytic DBMS for real-time computations and queries

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

a hierachical model (tree) can be imposed

Relational DBMS

Time Series DBMS

Document store

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	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Website

Technical documentation

Developer

Sachin Sinha, BangDB

BigObject, Inc.

Cognitect

The Linux Foundation

since July 2017

Initial release

2012

2015

2012

2017

2009

Current release

BangDB 2.0, October 2021

1.0.6735, June 2023

2.4.1, August 2020

License

Commercial or Open Source

Open Source

BSD 3

commercial

free community edition available

commercial

limited edition free

Open Source

Apache Version 2.0

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, Scala

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

Linux
macOS

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

fluentd
ODBC
RESTful HTTP API

RESTful HTTP API

gRPC
HTTP REST
WebSocket

Supported programming languages

C
C#
C++
Java
Python

Clojure
Java

Java
Scala

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

Lua

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

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

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, optimistic concurrency control

yes

Read/write lock on objects (tables, trees)

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)

Using Apache Lucene

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

User concepts

Access control

yes (enterprise version only)

yes

users and table-level permissions

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