DBMS > FatDB vs. Sphinx vs. Sqrrl vs. Tkrzw

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

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

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

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

Primary database model

Document store
Key-value store

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

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

Website

sphinxsearch.com

sqrrl.com

dbmx.net/tkrzw

Technical documentation

sphinxsearch.com/docs

Developer

FatCloud

Sphinx Technologies Inc.

Amazon

originally Sqrrl Data, Inc.

Mikio Hirabayashi

Initial release

2012

2001

2012

2020

Current release

3.5.1, February 2023

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

GPL version 2, commercial licence available

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++

Java

C++

Server operating systems

Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux

Linux
macOS

Data scheme

schema-free

yes

schema-free

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

Via inetgration in SQL Server

SQL-like query language (SphinxQL)

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Proprietary protocol

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

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

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

via applications

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

selectable replication factor

making use of Hadoop

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

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

Transaction concepts

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

Atomic updates per row, document, or graph entity

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

using specific database classes

User concepts

Access control

Can implement custom security layer via applications

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

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More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
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