DBMS > BigObject vs. Citus vs. SiriDB vs. Sphinx vs. YottaDB

System Properties Comparison BigObject vs. Citus vs. SiriDB vs. Sphinx vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

Open Source Time Series DBMS

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

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Secondary database models

Document store

Relational DBMS

using the Octo plugin

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

Technical documentation

docs.bigobject.io

docs.citusdata.com

docs.siridb.com

sphinxsearch.com/docs

yottadb.com/resources/documentation

Developer

BigObject, Inc.

Cesbit

Sphinx Technologies Inc.

YottaDB, LLC

Initial release

2015

2010

2017

2001

Current release

8.1, December 2018

3.5.1, February 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

AGPL, commercial license also available

Open Source

MIT License

Open Source

GPL version 2, commercial licence available

Open Source

AGPL 3.0

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++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Docker
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data

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

full-text index on all search fields

SQL

Support of SQL

SQL-like DML and DDL statements

yes

standard, with numerous extensions

SQL-like query language (SphinxQL)

by using the Octo plugin

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

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

HTTP API

Proprietary protocol

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

Lua

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

other methods possible by using 3rd party extensions

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

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

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple rights management via user accounts

Users and groups based on OS-security mechanisms

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More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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