DBMS > Amazon CloudSearch vs. MonetDB vs. Riak TS vs. RocksDB vs. Teradata

System Properties Comparison Amazon CloudSearch vs. MonetDB vs. Riak TS vs. RocksDB vs. Teradata

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

A relational database management system that stores data in columns

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

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

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

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

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

aws.amazon.com/cloudsearch

www.monetdb.org

rocksdb.org

www.teradata.com

Technical documentation

docs.aws.amazon.com/cloudsearch

www.monetdb.org/Documentation

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

github.com/facebook/rocksdb/wiki

docs.teradata.com

Developer

Amazon

MonetDB BV

Open Source, formerly Basho Technologies

Facebook, Inc.

Teradata

Initial release

2012

2004

2015

2013

1984

Current release

Dec2023 (11.49), December 2023

3.0.0, September 2022

8.11.4, April 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Erlang

C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X

Linux

hosted
Linux

Data scheme

yes

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

all search fields are automatically indexed

yes

restricted

yes

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

SQL

Support of SQL

yes

SQL 2003 with some extensions

yes, limited

yes

SQL 2016 + extensions

APIs and other access methods

HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP API
Native Erlang Interface

C++ API
Java API

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

Supported programming languages

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

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
C++
Go
Java
Perl
Python
Ruby

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

Server-side scripts

Stored procedures

yes, in SQL, C, R

Erlang

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding via remote tables

Sharding

horizontal partitioning

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

none

Source-replica replication available in experimental status

selectable replication factor

yes

Multi-source replication
Source-replica replication

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

Foreign keys

Referential integrity

yes

links between datasets can be stored

yes

Transaction concepts

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

ACID

yes

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

authentication via encrypted signatures

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.