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DBMS > HEAVY.AI vs. Heroic vs. KeyDB vs. OpenTSDB

System Properties Comparison HEAVY.AI vs. Heroic vs. KeyDB vs. OpenTSDB

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonHeroic  Xexclude from comparisonKeyDB  Xexclude from comparisonOpenTSDB  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsScalable Time Series DBMS based on HBase
Primary database modelRelational DBMSTime Series DBMSKey-value storeTime Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.41
Rank#153  Overall
#71  Relational DBMS
Score0.13
Rank#335  Overall
#29  Time Series DBMS
Score0.63
Rank#232  Overall
#32  Key-value stores
Score1.59
Rank#140  Overall
#12  Time Series DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
github.com/­spotify/­heroicgithub.com/­Snapchat/­KeyDB
keydb.dev
opentsdb.net
Technical documentationdocs.heavy.aispotify.github.io/­heroicdocs.keydb.devopentsdb.net/­docs/­build/­html/­index.html
DeveloperHEAVY.AI, Inc.SpotifyEQ Alpha Technology Ltd.currently maintained by Yahoo and other contributors
Initial release2016201420192011
Current release5.10, January 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0Open Source infoBSD-3Open Source infoLGPL
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 CUDAJavaC++Java
Server operating systemsLinuxLinuxLinux
Windows
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesnumeric data for metrics, strings for tags
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 indexesnoyes infovia Elasticsearchyes infoby using the Redis Search moduleno
SQL infoSupport of SQLyesnonono
APIs and other access methodsJDBC
ODBC
Thrift
Vega
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Proprietary protocol infoRESP - REdis Serialization ProtocoHTTP API
Telnet API
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Erlang
Go
Java
Python
R
Ruby
Server-side scripts infoStored proceduresnonoLuano
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesMulti-source replication
Source-replica replication
selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoOptimistic locking, atomic execution of commands blocks and scriptsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardsimple password-based access control and ACLno

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

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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Recent citations in the news

5 Q’s for Mike Flaxman, Vice President of Heavy.AI
15 August 2024, Center for Data Innovation

HEAVY.AI Accelerates Big Data Analytics with Vultr's High-Performance GPU Cloud Infrastructure
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Dr. Mike Flaxman, VP or Product Management at HEAVY.AI – Interview Series
19 September 2024, Unite.AI

HEAVY.AI Accelerates Big Data Analytics with Vultr’s High-Performance GPU Cloud Infrastructure
11 September 2024, insideBIGDATA

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19 April 2023, Business Wire

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12 May 2022, TechCrunch

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