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DBMS > Brytlyt vs. DataFS vs. HEAVY.AI vs. TimescaleDB

System Properties Comparison Brytlyt vs. DataFS vs. HEAVY.AI vs. TimescaleDB

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonDataFS  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSObject oriented DBMSRelational DBMSTime Series DBMS
Secondary database modelsGraph DBMSSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitebrytlyt.ionewdatabase.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.timescale.com
Technical documentationdocs.brytlyt.iodev.mobiland.com/­Overview.xspdocs.heavy.aidocs.timescale.com
DeveloperBrytlytMobiland AGHEAVY.AI, Inc.Timescale
Initial release2016201820162017
Current release5.0, August 20231.1.263, October 20225.10, January 20222.13.0, November 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; enterprise edition availableOpen 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, C++ and CUDAC++ and CUDAC
Server operating systemsLinux
OS X
Windows
WindowsLinuxLinux
OS X
Windows
Data schemeyesClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yesyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, 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.yes infospecific XML-type available, but no XML query functionality.nonoyes
Secondary indexesyesnonoyes
SQL infoSupport of SQLyesnoyesyes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
.NET Client API
Proprietary client DLL
WinRT client
JDBC
ODBC
Thrift
Vega
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
C
C#
C++
VB.Net
All languages supporting JDBC/ODBC/Thrift
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesno, except callback-events from server when changes happenednoyes
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemSharding infoRound robinyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
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.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardWindows-Profilefine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
BrytlytDataFSHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022TimescaleDB
Recent citations in the news

Brytlyt releases version 5.0, introducing a more intuitive, intelligent and flexible analytics platform
1 August 2023, PR Newswire

London data analytics startup Brytlyt raises €4.43M from Amsterdam-based Finch Capital, others
22 December 2021, Silicon Canals

Brytlyt Secures $4M in Series A Funding
20 May 2020, Datanami

Brytlyt becomes NVIDIA Inception Premier Partner
31 January 2023, PR Newswire

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HEAVY.AI Partners with Bain, Maxar, and Nvidia to Provide Digital Twins for Telecom Networks
16 February 2023, Datanami

The insideBIGDATA IMPACT 50 List for Q4 2023
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Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
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