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DBMS > HEAVY.AI vs. Lovefield vs. Tarantool vs. Valentina Server

System Properties Comparison HEAVY.AI vs. Lovefield vs. Tarantool vs. Valentina Server

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonLovefield  Xexclude from comparisonTarantool  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareEmbeddable relational database for web apps written in pure JavaScriptIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsObject-relational database and reports server
Primary database modelRelational DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
google.github.io/­lovefieldwww.tarantool.iowww.valentina-db.net
Technical documentationdocs.heavy.aigithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdwww.tarantool.io/­en/­docvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperHEAVY.AI, Inc.GoogleVKParadigma Software
Initial release2016201420081999
Current release5.10, January 20222.1.12, February 20172.10.0, May 20225.7.5
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprisecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAJavaScriptC and C++
Server operating systemsLinuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariBSD
Linux
macOS
Linux
OS X
Windows
Data schemeyesyesFlexible 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.nonono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLyesSQL-like query language infovia JavaScript builder patternFull-featured ANSI SQL supportyes
APIs and other access methodsJDBC
ODBC
Thrift
Vega
Open binary protocolODBC
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
JavaScriptC
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnonoLua, C and SQL stored proceduresyes
TriggersnoUsing read-only observersyes, before/after data modification events, on replication events, client session eventsyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinnoneSharding, 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 replicationnoneAsynchronous 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 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 integritynoyesyesyes
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 transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing MemoryDByes, full featured in-memory storage engine with persistenceyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
fine grained access rights according to SQL-standard

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022LovefieldTarantoolValentina Server
DB-Engines blog posts

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

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