DBMS > Realm vs. ReductStore vs. Sphinx vs. STSdb

System Properties Comparison Realm vs. ReductStore vs. Sphinx vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

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

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

realm.io

github.com/reductstore
www.reduct.store

sphinxsearch.com

github.com/STSSoft/STSdb4

Technical documentation

realm.io/docs

www.reduct.store/docs

sphinxsearch.com/docs

Developer

Realm, acquired by MongoDB in May 2019

ReductStore LLC

Sphinx Technologies Inc.

STS Soft SC

Initial release

2014

2023

2001

2011

Current release

1.9, March 2024

3.5.1, February 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Business Source License 1.1

Open Source

GPL version 2, commercial licence available

Open Source

GPLv2, commercial license 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++, Rust

C++

Server operating systems

Android
Backend: server-less
iOS
Windows

Docker
Linux
macOS
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

SQL

Support of SQL

SQL-like query language (SphinxQL)

APIs and other access methods

HTTP API

Proprietary protocol

.NET Client API

Supported programming languages

.Net
Java

with Android only
Objective-C
React Native
Swift

C++
JavaScript (Node.js)
Python
Rust

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
Java

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

In-Memory realm

User concepts

Access control

yes

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