DBMS > HyperSQL vs. KeyDB vs. Sphinx

System Properties Comparison HyperSQL vs. KeyDB vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

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

Primary database model

Relational DBMS

Key-value store

Search engine

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

Score	3.90
Rank	#85	Overall
	#46	Relational DBMS

Score	0.80
Rank	#219	Overall
	#31	Key-value stores

Score	6.03
Rank	#60	Overall
	#6	Search engines

Website

hsqldb.org

github.com/Snapchat/KeyDB
keydb.dev

sphinxsearch.com

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

docs.keydb.dev

sphinxsearch.com/docs

Developer

EQ Alpha Technology Ltd.

Sphinx Technologies Inc.

Initial release

2001

2019

2001

Current release

2.7.2, June 2023

3.5.1, February 2023

License

Commercial or Open Source

Open Source

based on BSD license

Open Source

BSD-3

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

Java

C++

Server operating systems

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

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

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

yes

SQL-like query language (SphinxQL)

APIs and other access methods

HTTP API

JDBC via HTTP
JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC
Java

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++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Java, SQL

Lua

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

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

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

fine grained access rights according to SQL-standard

simple password-based access control and ACL

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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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