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DBMS > HEAVY.AI vs. Riak KV vs. Sqrrl vs. TimescaleDB

System Properties Comparison HEAVY.AI vs. Riak KV vs. Sqrrl vs. TimescaleDB

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonRiak KV  Xexclude from comparisonSqrrl  Xexclude from comparisonTimescaleDB  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareDistributed, fault tolerant key-value storeAdaptable, secure NoSQL built on Apache AccumuloA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesDocument store
Graph DBMS
Key-value store
Wide column store
Time Series DBMS
Secondary database modelsSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
sqrrl.comwww.timescale.com
Technical documentationdocs.heavy.aiwww.tiot.jp/­riak-docs/­riak/­kv/­latestdocs.timescale.com
DeveloperHEAVY.AI, Inc.OpenSource, formerly Basho TechnologiesAmazon infooriginally Sqrrl Data, Inc.Timescale
Initial release2016200920122017
Current release5.10, January 20223.2.0, December 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache version 2, commercial enterprise editioncommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAErlangJavaC
Server operating systemsLinuxLinux
OS X
LinuxLinux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyes
Secondary indexesnorestrictedyesyes
SQL infoSupport of SQLyesnonoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
Thrift
Vega
HTTP API
Native Erlang Interface
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoErlangnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyes infopre-commit hooks and post-commit hooksnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinSharding infono "single point of failure"Sharding infomaking use of Hadoopyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationselectable replication factorselectable replication factor infomaking use of HadoopSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency
Foreign keys infoReferential integritynono infolinks between data sets can be storednoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoAtomic updates per row, document, or graph entityACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardyes, using Riak SecurityCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)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 2022Riak KVSqrrlTimescaleDB
Recent citations in the news

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, Business Wire

HEAVY.AI Partners with Bain, Maxar, and Nvidia to Provide Digital Twins for Telecom Networks
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26 August 2018, InfoQ.com

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15 September 2014, Data Center Knowledge

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23 February 2024, Dark Reading

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23 January 2018, CNBC

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8 June 2023, CISO Mag

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4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
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