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DBMS > Microsoft Azure AI Search vs. Quasardb vs. Tarantool vs. Transwarp Hippo

System Properties Comparison Microsoft Azure AI Search vs. Quasardb vs. Tarantool vs. Transwarp Hippo

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Editorial information provided by DB-Engines
NameMicrosoft Azure AI Search  Xexclude from comparisonQuasardb  Xexclude from comparisonTarantool  Xexclude from comparisonTranswarp Hippo  Xexclude from comparison
DescriptionSearch-as-a-service for web and mobile app developmentDistributed, high-performance timeseries databaseIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsCloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets
Primary database modelSearch engineTime Series DBMSDocument store
Key-value store
Relational DBMS
Vector DBMS
Secondary database modelsVector DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.75
Rank#58  Overall
#7  Search engines
Score0.13
Rank#332  Overall
#28  Time Series DBMS
Score1.63
Rank#139  Overall
#25  Document stores
#24  Key-value stores
#65  Relational DBMS
Score0.00
Rank#385  Overall
#16  Vector DBMS
Websiteazure.microsoft.com/­en-us/­services/­searchquasar.aiwww.tarantool.iowww.transwarp.cn/­en/­subproduct/­hippo
Technical documentationlearn.microsoft.com/­en-us/­azure/­searchdoc.quasar.ai/­masterwww.tarantool.io/­en/­doc
DeveloperMicrosoftquasardbVK
Initial release2015200920082023
Current releaseV13.14.1, January 20242.10.0, May 20221.0, May 2023
License infoCommercial or Open Sourcecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprisecommercial
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++C and C++C++
Server operating systemshostedBSD
Linux
OS X
Windows
BSD
Linux
macOS
Linux
macOS
Data schemeyesschema-freeFlexible 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 binarystring, double, decimal, uuid, integer, blob, boolean, datetimeVector, Numeric and String
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 tagsyesno
SQL infoSupport of SQLnoSQL-like query languageFull-featured ANSI SQL supportno
APIs and other access methodsRESTful HTTP APIHTTP APIOpen binary protocolRESTful HTTP API
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
C++
Java
Python
Server-side scripts infoStored proceduresnonoLua, C and SQL stored proceduresno
Triggersnonoyes, before/after data modification events, on replication events, client session eventsno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infoconsistent hashingSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceSource-replica replication with selectable replication factorAsynchronous 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 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
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyes infoby using LevelDByes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeyes, full featured in-memory storage engine with persistenceyes
User concepts infoAccess controlyes infousing Azure authenticationCryptographically strong user authentication and audit trailAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
Role based access control and fine grained access rights

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More resources
Microsoft Azure AI SearchQuasardbTarantoolTranswarp Hippo
DB-Engines blog posts

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

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