DBMS > Apache Impala vs. Sphinx vs. STSdb vs. Transbase

System Properties Comparison Apache Impala vs. Sphinx vs. STSdb vs. Transbase

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

impala.apache.org

sphinxsearch.com

github.com/STSSoft/STSdb4

www.transaction.de/en/products/transbase.html

Technical documentation

impala.apache.org/impala-docs.html

sphinxsearch.com/docs

www.transaction.de/en/products/transbase/features.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Sphinx Technologies Inc.

STS Soft SC

Transaction Software GmbH

Initial release

2013

2001

2011

1987

Current release

4.1.0, June 2022

3.5.1, February 2023

4.0.8, September 2015

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPL version 2, commercial licence available

Open Source

GPLv2, commercial license available

commercial

free development license

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++

Server operating systems

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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 DML and DDL statements

SQL-like query language (SphinxQL)

yes

APIs and other access methods

JDBC
ODBC

Proprietary protocol

.NET Client API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
Java

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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.

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

show all

Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

Switching From Sphinx to MkDocs Documentation — What Did I Gain and Lose
2 February 2024, Towards Data Science

5 Powerful Alternatives to Elasticsearch
25 April 2024, Insider Monkey

Manticore is a Faster Alternative to Elasticsearch in C++
25 July 2022, hackernoon.com

Royal Mail stamp prices could rise, warns Czech Sphinx
3 June 2024, Proactive Investors UK

Perplexity AI: From Its Use To Operation, Everything You Need To Know About Google's Newest Challenger
11 January 2024, Free Press Journal

provided by Google News

Share this page