DBMS > Apache Phoenix vs. Riak TS vs. searchxml vs. Sphinx

System Properties Comparison Apache Phoenix vs. Riak TS vs. searchxml vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

DBMS for structured and unstructured content wrapped with an application server

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

Primary database model

Relational DBMS

Time Series DBMS

Native XML DBMS
Search engine

Search engine

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

phoenix.apache.org

www.searchxml.net/category/products

sphinxsearch.com

Technical documentation

phoenix.apache.org

www.tiot.jp/riak-docs/riak/ts/latest

www.searchxml.net/support/handouts

sphinxsearch.com/docs

Developer

Apache Software Foundation

Open Source, formerly Basho Technologies

informationpartners gmbh

Sphinx Technologies Inc.

Initial release

2014

2015

2001

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

3.0.0, September 2022

1.0

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

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

Erlang

C++

Server operating systems

Linux
Unix
Windows

Linux
OS X

Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

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.

yes

Secondary indexes

yes

restricted

yes

full-text index on all search fields

SQL

Support of SQL

yes

yes, limited

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC

HTTP API
Native Erlang Interface

RESTful HTTP API
WebDAV
XQuery
XSLT

Proprietary protocol

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C++

most other programming languages supported via APIs

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

Erlang

yes

on the application server

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

yes

sychronisation to multiple collections

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

ACID

multiple readers, single writer

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.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Domain, group and role-based access control at the document level and for application services

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More resources

DB-Engines blog posts

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11 August 2021, Krishna Maheshwari (sponsor)

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4 February 2013, Paul Andlinger

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