DBMS > RocksDB vs. SAP SQL Anywhere vs. Solr vs. Splunk vs. Teradata

System Properties Comparison RocksDB vs. SAP SQL Anywhere vs. Solr vs. Splunk vs. Teradata

Editorial information provided by DB-Engines

Name

Description

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

A widely used distributed, scalable search engine based on Apache Lucene

Analytics Platform for Big Data

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

rocksdb.org

www.sap.com/products/technology-platform/sql-anywhere.html

solr.apache.org

www.splunk.com

www.teradata.com

Technical documentation

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_SQL_Anywhere

solr.apache.org/resources.html

docs.splunk.com/Documentation/Splunk

docs.teradata.com

Developer

Facebook, Inc.

SAP

formerly Sybase

Apache Software Foundation

Splunk Inc.

Teradata

Initial release

2013

1992

2006

2003

1984

Current release

8.11.4, April 2024

17, July 2015

9.6.0, April 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

BSD

commercial

Open Source

Apache Version 2

commercial

Limited free edition and free developer edition available

commercial

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

Server operating systems

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux
OS X
Solaris
Windows

hosted
Linux

Data scheme

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

Solr Parallel SQL Interface

Splunk Search Processing Language for search commands

yes

SQL 2016 + extensions

APIs and other access methods

C++ API
Java API

ADO.NET
HTTP API
JDBC
ODBC

Java API
RESTful HTTP/JSON API

HTTP REST

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C#
Java
JavaScript
PHP
Python
Ruby

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes, in C/C++, Java, .Net or Perl

Java plugins

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Database mirroring

yes

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

optimistic locking

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Access rights for users and roles

fine grained access rights according to SQL-standard

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