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DBMS > Hazelcast vs. Microsoft Azure AI Search vs. Tarantool vs. TigerGraph

System Properties Comparison Hazelcast vs. Microsoft Azure AI Search vs. Tarantool vs. TigerGraph

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonTarantool  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionA widely adopted in-memory data gridSearch-as-a-service for web and mobile app developmentIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelKey-value storeSearch engineDocument store
Key-value store
Relational DBMS
Graph DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Vector DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.72
Rank#59  Overall
#6  Key-value stores
Score5.75
Rank#58  Overall
#7  Search engines
Score1.63
Rank#139  Overall
#25  Document stores
#24  Key-value stores
#65  Relational DBMS
Score1.44
Rank#152  Overall
#14  Graph DBMS
Websitehazelcast.comazure.microsoft.com/­en-us/­services/­searchwww.tarantool.iowww.tigergraph.com
Technical documentationhazelcast.org/­imdg/­docslearn.microsoft.com/­en-us/­azure/­searchwww.tarantool.io/­en/­docdocs.tigergraph.com
DeveloperHazelcastMicrosoftVK
Initial release2008201520082017
Current release5.3.6, November 2023V12.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprisecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++C++
Server operating systemsAll OS with a Java VMhostedBSD
Linux
macOS
Linux
Data schemeschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyesyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyes
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.yes infothe object must implement a serialization strategynonono
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoFull-featured ANSI SQL supportSQL-like query language (GSQL)
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP APIOpen binary protocolGSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
Java
JavaScript
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C++
Java
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor ServicesnoLua, C and SQL stored proceduresyes
Triggersyes infoEventsnoyes, before/after data modification events, on replication events, client session eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding, 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 infoReplicated Mapyes infoImplicit feature of the cloud serviceAsynchronous 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 methodsyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate 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 integritynonoyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes, full featured in-memory storage engine with persistenceno
User concepts infoAccess controlRole-based access controlyes infousing Azure authenticationAccess 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

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More resources
HazelcastMicrosoft Azure AI SearchTarantoolTigerGraph
DB-Engines blog posts

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

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