DBMS > Microsoft Azure AI Search vs. Riak KV vs. STSdb vs. TempoIQ vs. Teradata Aster

System Properties Comparison Microsoft Azure AI Search vs. Riak KV vs. STSdb vs. TempoIQ vs. Teradata Aster

Editorial information provided by DB-Engines

Name

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

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

Distributed, fault tolerant key-value store

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

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

Platform for big data analytics on multistructured data sources and types

Primary database model

Search engine

Key-value store

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

Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Vector DBMS

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

Score	5.59
Rank	#63	Overall
	#7	Search engines

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

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

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

github.com/STSSoft/STSdb4

tempoiq.com (offline)

Technical documentation

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

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

Developer

Microsoft

OpenSource, formerly Basho Technologies

STS Soft SC

TempoIQ

Teradata

Initial release

2015

2009

2011

2012

2005

Current release

3.2.0, December 2022

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPLv2, commercial license available

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

Server operating systems

hosted

Linux
OS X

Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

in Aster File Store

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

HTTP API
Native Erlang Interface

.NET Client API

HTTP API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C#
Java
JavaScript
Python

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

C#
Java
JavaScript

Node.js
Python
Ruby

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

Erlang

R packages

Triggers

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"

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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.

User concepts

Access control

yes

using Azure authentication

yes, using Riak Security

simple authentication-based access control

fine grained access rights according to SQL-standard

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