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DBMS > HEAVY.AI vs. Microsoft Azure AI Search vs. Rockset vs. Tarantool

System Properties Comparison HEAVY.AI vs. Microsoft Azure AI Search vs. Rockset vs. Tarantool

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonRockset  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareSearch-as-a-service for web and mobile app developmentA scalable, reliable search and analytics service in the cloud, built on RocksDBIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSSearch engineDocument storeDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMSVector DBMSRelational DBMS
Search engine
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.41
Rank#153  Overall
#71  Relational DBMS
Score5.75
Rank#58  Overall
#7  Search engines
Score1.07
Rank#180  Overall
#31  Document stores
Score1.63
Rank#139  Overall
#25  Document stores
#24  Key-value stores
#65  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­en-us/­services/­searchrockset.comwww.tarantool.io
Technical documentationdocs.heavy.ailearn.microsoft.com/­en-us/­azure/­searchdocs.rockset.comwww.tarantool.io/­en/­doc
DeveloperHEAVY.AI, Inc.MicrosoftRocksetVK
Initial release2016201520192008
Current release5.10, January 2022V12.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAC++C and C++
Server operating systemsLinuxhostedhostedBSD
Linux
macOS
Data schemeyesyesschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesdynamic typingstring, 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.nonono infoingestion from XML files supportedno
Secondary indexesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLyesnoRead-only SQL queries, including JOINsFull-featured ANSI SQL support
APIs and other access methodsJDBC
ODBC
Thrift
Vega
RESTful HTTP APIHTTP RESTOpen binary protocol
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C#
Java
JavaScript
Python
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnononoLua, C and SQL stored procedures
Triggersnononoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinSharding infoImplicit feature of the cloud serviceAutomatic shardingSharding, 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 nodesMulti-source replicationyes infoImplicit feature of the cloud serviceyesAsynchronous 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 methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual 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 datanononoACID, 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 persistentyesyesyesyes, write ahead logging
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 persistence
User concepts infoAccess controlfine grained access rights according to SQL-standardyes infousing Azure authenticationAccess rights for users and organizations can be defined via Rockset consoleAccess 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
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure AI SearchRocksetTarantool
DB-Engines blog posts

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

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Recent citations in the news

Dr. Mike Flaxman, VP or Product Management at HEAVY.AI – Interview Series
19 September 2024, Unite.AI

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HEAVY.AI Accelerates Big Data Analytics with Vultr’s High-Performance GPU Cloud Infrastructure
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