DBMS > Apache Phoenix vs. Microsoft Azure AI Search vs. OpenSearch vs. Riak KV vs. TempoIQ

System Properties Comparison Apache Phoenix vs. Microsoft Azure AI Search vs. OpenSearch vs. Riak KV vs. TempoIQ

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

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

Search-as-a-service for web and mobile app development

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

Distributed, fault tolerant key-value store

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Relational DBMS

Search engine

Key-value store

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

Time Series DBMS

Secondary database models

Vector DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	16.36
Rank	#37	Overall
	#4	Search engines

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

phoenix.apache.org

azure.microsoft.com/en-us/services/search

github.com/opensearch-project
opensearch.org

tempoiq.com (offline)

Technical documentation

phoenix.apache.org

learn.microsoft.com/en-us/azure/search

opensearch.org/docs/latest

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

Developer

Apache Software Foundation

Microsoft

Amazon Web Services

OpenSource, formerly Basho Technologies

TempoIQ

Initial release

2014

2015

2021

2009

2012

Current release

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

2.5.0, January 2023

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

Open Source

Apache version 2, commercial enterprise edition

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.

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Implementation language

Java

Erlang

Server operating systems

Linux
Unix
Windows

hosted

All OS with a Java VM

Linux
OS X

Data scheme

yes

late-bound, schema-on-read capabilities

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

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

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC

RESTful HTTP API

Java API
RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

HTTP API

Supported programming languages

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

C#
Java
JavaScript
Python

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

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#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Erlang

Triggers

yes

by using the 'percolation' feature

yes

pre-commit hooks and post-commit hooks

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

yes

selectable replication factor

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

Immediate Consistency

Eventual Consistency

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

Eventual Consistency

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

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

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

yes

using Azure authentication

yes, using Riak Security

simple authentication-based access control

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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