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DBMS > Databricks vs. FatDB vs. HEAVY.AI vs. Hypertable

System Properties Comparison Databricks vs. FatDB vs. HEAVY.AI vs. Hypertable

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonHypertable  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A .NET NoSQL DBMS that can integrate with and extend SQL Server.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareAn open source BigTable implementation based on distributed file systems such as Hadoop
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Relational DBMSWide column store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Websitewww.databricks.comgithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationdocs.databricks.comdocs.heavy.ai
DeveloperDatabricksFatCloudHEAVY.AI, Inc.Hypertable Inc.
Initial release2013201220162009
Current release5.10, January 20220.9.8.11, March 2016
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoGNU version 3. Commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#C++ and CUDAC++
Server operating systemshostedWindowsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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.yesno
Secondary indexesyesyesnorestricted infoonly exact value or prefix value scans
SQL infoSupport of SQLwith Databricks SQLno infoVia inetgration in SQL Serveryesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Thrift
Vega
C++ API
Thrift
Supported programming languagesPython
R
Scala
C#All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infovia applicationsnono
Triggersyes infovia applicationsnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorMulti-source replicationselectable replication factor on file system level
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
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.noyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardno
More information provided by the system vendor
DatabricksFatDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Hypertable
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksFatDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Hypertable
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