DBMS > ObjectBox vs. Percona Server for MongoDB vs. Sphinx vs. VoltDB

System Properties Comparison ObjectBox vs. Percona Server for MongoDB vs. Sphinx vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Extremely fast embedded database for small devices, IoT and Mobile

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Time Series DBMS

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

Score	1.22
Rank	#172	Overall
	#5	Object oriented DBMS

Score	0.55
Rank	#253	Overall
	#39	Document stores

Score	6.03
Rank	#60	Overall
	#6	Search engines

Score	1.46
Rank	#159	Overall
	#74	Relational DBMS

Website

objectbox.io

www.percona.com/mongodb/software/percona-server-for-mongodb

sphinxsearch.com

www.voltdb.com

Technical documentation

docs.objectbox.io

docs.percona.com/percona-distribution-for-mongodb

sphinxsearch.com/docs

docs.voltdb.com

Developer

ObjectBox Limited

Percona

Sphinx Technologies Inc.

VoltDB Inc.

Initial release

2017

2015

2001

2010

Current release

3.4.10-2.10, November 2017

3.5.1, February 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

GPL Version 2

Open Source

GPL version 2, commercial licence available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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 and C++

C++

Java, C++

Server operating systems

Android
iOS
Linux
macOS
Windows

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X

for development

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language (SphinxQL)

yes

only a subset of SQL 99

APIs and other access methods

Proprietary native API

proprietary protocol using JSON

Proprietary protocol

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

JavaScript

Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

online/offline synchronization between client and server

Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

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

yes

Snapshots and command logging

In-memory capabilities

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

yes

via In-Memory Engine

User concepts

Access control

yes

Access rights for users and roles

Users and roles with access to stored procedures

More information provided by the system vendor

News

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

Vector Database Release for Flutter / Dart + Python
13 June 2023

SQLite and SQLite alternatives – a comprehensive overview
7 June 2023

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More resources

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