DBMS > KeyDB vs. ObjectBox vs. SiriDB vs. Sphinx

System Properties Comparison KeyDB vs. ObjectBox vs. SiriDB vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Open Source Time Series DBMS

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

Primary database model

Key-value store

Object oriented DBMS
Vector DBMS

Time Series DBMS

Search engine

Secondary database models

Time Series DBMS

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

Score	0.63
Rank	#232	Overall
	#32	Key-value stores

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

github.com/Snapchat/KeyDB
keydb.dev

github.com/objectbox
objectbox.io

siridb.com

sphinxsearch.com

Technical documentation

docs.keydb.dev

docs.objectbox.io

docs.siridb.com

sphinxsearch.com/docs

Developer

EQ Alpha Technology Ltd.

ObjectBox Limited

Cesbit

Sphinx Technologies Inc.

Initial release

2019

2017

2001

Current release

4.0 (May 2024)

3.5.1, February 2023

License

Commercial or Open Source

Open Source

BSD-3

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

MIT License

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 and C++

C++

Server operating systems

Linux

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes, plus "flex" map-like types

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.

Secondary indexes

yes

by using the Redis Search module

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language (SphinxQL)

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protoco

Proprietary native API

HTTP API

Proprietary protocol

Supported programming languages

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

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

Server-side scripts

Stored procedures

Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Data sync between devices allowing occasional connected databases to work completely offline

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

User concepts

Access control

simple password-based access control and ACL

yes

simple rights management via user accounts

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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More resources

DB-Engines blog posts

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