DBMS > Bangdb vs. Citus vs. Realm vs. Sadas Engine vs. Sphinx

System Properties Comparison Bangdb vs. Citus vs. Realm vs. Sadas Engine vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Document store
Graph DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

Document store

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	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

Technical documentation

docs.bangdb.com

docs.citusdata.com

realm.io/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

sphinxsearch.com/docs

Developer

Sachin Sinha, BangDB

Realm, acquired by MongoDB in May 2019

SADAS s.r.l.

Sphinx Technologies Inc.

Initial release

2012

2010

2014

2006

2001

Current release

BangDB 2.0, October 2021

8.1, December 2018

8.0

3.5.1, February 2023

License

Commercial or Open Source

Open Source

BSD 3

Open Source

AGPL, commercial license also available

Open Source

commercial

free trial version available

Open Source

GPL version 2, commercial licence available

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++

C++

Server operating systems

Linux

Android
Backend: server-less
iOS
Windows

AIX
Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

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

specific XML type available, but no XML query functionality

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

full-text index on all search fields

SQL

Support of SQL

SQL like support with command line tool

yes

standard, with numerous extensions

yes

SQL-like query language (SphinxQL)

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC
Proprietary protocol

Proprietary protocol

Supported programming languages

C
C#
C++
Java
Python

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
Java

with Android only
Objective-C
React Native
Swift

.Net
C
C#
C++
Groovy
Java
PHP
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

runs within the applications so server-side scripts are unnecessary

Triggers

yes, Notifications (with Streaming only)

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

Sharding

none

horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

other methods possible by using 3rd party extensions

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

The original contents of fields are not stored in the Sphinx index.

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

In-Memory realm

yes

managed by 'Learn by Usage'

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

yes

Access rights for users, groups and roles according to SQL-standard

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