DBMS > Apache Druid vs. Riak TS vs. SAP HANA vs. Sphinx

System Properties Comparison Apache Druid vs. Riak TS vs. SAP HANA vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

In-memory, column based data store. Available as appliance or cloud service

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

Primary database model

Relational DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

Search engine

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

druid.apache.org

www.sap.com/products/hana.html

sphinxsearch.com

Technical documentation

druid.apache.org/docs/latest/design

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

help.sap.com/hana

sphinxsearch.com/docs

Developer

Apache Software Foundation and contributors

Open Source, formerly Basho Technologies

SAP

Sphinx Technologies Inc.

Initial release

2012

2015

2010

2001

Current release

29.0.1, April 2024

3.0.0, September 2022

2.0 SPS07 (April 4, 2023), April 2023

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

commercial

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

also available as a cloud based 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
OS X
Unix

Linux
OS X

Appliance or cloud-service

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-less columns are supported

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

restricted

yes

full-text index on all search fields

SQL

Support of SQL

SQL for querying

yes, limited

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

JDBC
ODBC

Proprietary protocol

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
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++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Erlang

SQLScript, R

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

yes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

yes

Transaction concepts

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

ACID

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

yes

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