DBMS > Microsoft Azure AI Search vs. NSDb vs. TimesTen vs. Vitess

System Properties Comparison Microsoft Azure AI Search vs. NSDb vs. TimesTen vs. Vitess

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

In-Memory RDBMS compatible to Oracle

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Search engine

Time Series DBMS

Relational DBMS

Secondary database models

Vector DBMS

Document store
Spatial DBMS

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

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

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

nsdb.io

www.oracle.com/database/technologies/related/timesten.html

vitess.io

Technical documentation

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

nsdb.io/Architecture

docs.oracle.com/database/timesten-18.1

vitess.io/docs

Developer

Microsoft

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

The Linux Foundation, PlanetScale

Initial release

2015

2017

1998

2013

Current release

11 Release 2 (11.2.2.8.0)

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0, commercial licenses available

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

Java, Scala

Server operating systems

hosted

Linux
macOS

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Docker
Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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 fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API

gRPC
HTTP REST
WebSocket

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C#
Java
JavaScript
Python

Java
Scala

C
C++
Java
PL/SQL

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

PL/SQL

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

by means of logfiles and checkpoints

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

yes

using Azure authentication

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Azure AI Studio Now Generally Available, Sporting New Models Both Big and Small
21 May 2024, Visual Studio Magazine

Microsoft beefs up Azure's arsenal of generative AI development tools
21 May 2024, SiliconANGLE News

Announcing updates to Azure AI Search to help organizations build and scale generative AI applications
4 April 2024, Microsoft

Microsoft Azure AI gains new LLMs, governance features
21 May 2024, InfoWorld

Microsoft Azure gets 'Models as a Service,' enhanced RAG offerings for enterprise generative AI
21 May 2024, ZDNet

provided by Google News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

provided by Google News

Share this page