DBMS > Netezza vs. OpenSearch vs. OpenTSDB vs. Riak KV vs. Sqrrl

System Properties Comparison Netezza vs. OpenSearch vs. OpenTSDB vs. Riak KV vs. Sqrrl

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

Data warehouse and analytics appliance part of IBM PureSystems

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Scalable Time Series DBMS based on HBase

Distributed, fault tolerant key-value store

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Vector DBMS

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

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

www.ibm.com/products/netezza

github.com/opensearch-project
opensearch.org

opentsdb.net

sqrrl.com

Technical documentation

opensearch.org/docs/latest

opentsdb.net/docs/build/html/index.html

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

Developer

IBM

Amazon Web Services

currently maintained by Yahoo and other contributors

OpenSource, formerly Basho Technologies

Amazon

originally Sqrrl Data, Inc.

Initial release

2000

2021

2011

2009

2012

Current release

2.5.0, January 2023

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

LGPL

Open Source

Apache version 2, commercial enterprise edition

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.

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Implementation language

Java

Erlang

Java

Server operating systems

Linux

included in appliance

All OS with a Java VM

Linux
Windows

Linux
OS X

Linux

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

All search fields are automatically indexed

restricted

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC
OLE DB

Java API
RESTful HTTP/JSON API

HTTP API
Telnet API

HTTP API
Native Erlang Interface

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

C
C++
Fortran
Java
Lua
Perl
Python
R

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Erlang
Go
Java
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

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

Erlang

Triggers

yes

by using the 'percolation' feature

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Sharding

no "single point of failure"

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

selectable replication factor

based on HBase

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

based on HBase

Eventual Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

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

ACID

Atomic updates per row, document, or graph entity

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.

User concepts

Access control

Users with fine-grained authorization concept

yes, using Riak Security

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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