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DBMS > Microsoft Azure AI Search vs. Quasardb vs. SiteWhere vs. Tarantool

System Properties Comparison Microsoft Azure AI Search vs. Quasardb vs. SiteWhere vs. Tarantool

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Editorial information provided by DB-Engines
NameMicrosoft Azure AI Search  Xexclude from comparisonQuasardb  Xexclude from comparisonSiteWhere  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionSearch-as-a-service for web and mobile app developmentDistributed, high-performance timeseries databaseM2M integration platform for persisting/querying time series dataIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelSearch engineTime Series DBMSTime Series DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsVector DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.71
Rank#64  Overall
#8  Search engines
Score0.19
Rank#327  Overall
#30  Time Series DBMS
Score0.06
Rank#367  Overall
#36  Time Series DBMS
Score1.67
Rank#150  Overall
#25  Document stores
#25  Key-value stores
#69  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­searchquasar.aigithub.com/­sitewhere/­sitewherewww.tarantool.io
Technical documentationlearn.microsoft.com/­en-us/­azure/­searchdoc.quasar.ai/­mastersitewhere1.sitewhere.io/­index.htmlwww.tarantool.io/­en/­doc
DeveloperMicrosoftquasardbSiteWhereVK
Initial release2015200920102008
Current releaseV13.14.1, January 20242.10.0, May 2022
License infoCommercial or Open Sourcecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoCommon Public Attribution License Version 1.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC and C++
Server operating systemshostedBSD
Linux
OS X
Windows
Linux
OS X
Windows
BSD
Linux
macOS
Data schemeyesschema-freepredefined schemeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyes infointeger and binaryyesstring, double, decimal, uuid, integer, blob, boolean, datetime
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono
Secondary indexesyesyes infowith tagsnoyes
SQL infoSupport of SQLnoSQL-like query languagenoFull-featured ANSI SQL support
APIs and other access methodsRESTful HTTP APIHTTP APIHTTP RESTOpen binary protocol
Supported programming languagesC#
Java
JavaScript
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnonoLua, C and SQL stored procedures
Triggersnonoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infoconsistent hashingSharding infobased on HBaseSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceSource-replica replication with selectable replication factorselectable replication factor infobased on HBaseAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyes infoby using LevelDByesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modenoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlyes infousing Azure authenticationCryptographically strong user authentication and audit trailUsers with fine-grained authorization conceptAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
Microsoft Azure AI SearchQuasardbSiteWhereTarantool
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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