DBMS > Sphinx vs. Sqrrl vs. Tkrzw vs. VoltDB

System Properties Comparison Sphinx vs. Sqrrl vs. Tkrzw vs. VoltDB

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Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

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

Adaptable, secure NoSQL built on Apache Accumulo

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

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

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Relational DBMS

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

Score	5.97
Rank	#56	Overall
	#5	Search engines

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

sphinxsearch.com

sqrrl.com

dbmx.net/tkrzw

www.voltdb.com

Technical documentation

sphinxsearch.com/docs

docs.voltdb.com

Developer

Sphinx Technologies Inc.

Amazon

originally Sqrrl Data, Inc.

Mikio Hirabayashi

VoltDB Inc.

Initial release

2001

2012

2020

2010

Current release

3.5.1, February 2023

0.9.3, August 2020

11.3, April 2022

License

Commercial or Open Source

Open Source

GPL version 2, commercial licence available

commercial

Open Source

Apache Version 2.0

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++

Java

C++

Java, C++

Server operating systems

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux

Linux
macOS

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 protocol

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

C++
Java
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

making use of Hadoop

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

making use of Hadoop

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

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Immediate Consistency

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

Atomic updates per row, document, or graph entity

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

using specific database classes

User concepts

Access control

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

Users and roles with access to stored procedures

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More resources

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The DB-Engines ranking includes now search engines
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