DBMS > Sphinx vs. SQLite vs. SQream DB vs. VictoriaMetrics

System Properties Comparison Sphinx vs. SQLite vs. SQream DB vs. VictoriaMetrics

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Editorial information provided by DB-Engines

Name

Description

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

Widely used embeddable, in-process RDBMS

a GPU-based, columnar RDBMS for big data analytics workloads

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Search engine

Relational DBMS

Time Series DBMS

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

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

Technical documentation

sphinxsearch.com/docs

www.sqlite.org/docs.html

docs.sqream.com

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Sphinx Technologies Inc.

Dwayne Richard Hipp

SQream Technologies

VictoriaMetrics

Initial release

2001

2000

2017

2018

Current release

3.5.1, February 2023

3.46.0 (23 May 2024), May 2024

2022.1.6, December 2022

v1.91, May 2023

License

Commercial or Open Source

Open Source

GPL version 2, commercial licence available

Open Source

Public Domain

commercial

Open Source

Apache Version 2.0

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++

C++, CUDA, Haskell, Java, Scala

Server operating systems

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

server-less

Linux

FreeBSD
Linux
macOS
OpenBSD

Data scheme

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

yes, ANSI Standard SQL Types

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

SQL-92 is not fully supported

yes

APIs and other access methods

Proprietary protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.Net
JDBC
ODBC

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

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