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DBMS > Databricks vs. HEAVY.AI vs. Typesense

System Properties Comparison Databricks vs. HEAVY.AI vs. Typesense

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonTypesense  Xexclude from comparison
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 high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelDocument store
Relational DBMS
Relational DBMSSearch engine
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
Score0.79
Rank#210  Overall
#14  Search engines
Websitewww.databricks.comgithub.com/­heavyai/­heavydb
www.heavy.ai
typesense.org
Technical documentationdocs.databricks.comdocs.heavy.aitypesense.org/­docs
DeveloperDatabricksHEAVY.AI, Inc.
Initial release201320162015
Current release5.10, January 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAC++
Server operating systemshostedLinuxLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free infopre-defined schema optional
Typing infopredefined data types such as float or dateyesyes
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 indexesyesnoyes
SQL infoSupport of SQLwith Databricks SQLyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
RESTful HTTP API
Supported programming languagesPython
R
Scala
All languages supporting JDBC/ODBC/Thrift
Python
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersno
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationMulti-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Typesense
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Typesense
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