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DBMS > Databricks vs. HEAVY.AI vs. Stardog vs. Yanza

System Properties Comparison Databricks vs. HEAVY.AI vs. Stardog vs. Yanza

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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 comparisonStardog  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded 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 high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationTime Series DBMS for IoT Applications
Primary database modelDocument store
Relational DBMS
Relational DBMSGraph DBMS
RDF store
Time Series DBMS
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
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitewww.databricks.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.stardog.comyanza.com
Technical documentationdocs.databricks.comdocs.heavy.aidocs.stardog.com
DeveloperDatabricksHEAVY.AI, Inc.Stardog-UnionYanza
Initial release2013201620102015
Current release5.10, January 20227.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availablecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentscommercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesnonono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAJava
Server operating systemshostedLinuxLinux
macOS
Windows
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free and OWL/RDFS-schema supportschema-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.yesnono infoImport/export of XML data possibleno
Secondary indexesyesnoyes infosupports real-time indexing in full-text and geospatialno
SQL infoSupport of SQLwith Databricks SQLyesYes, compatible with all major SQL variants through dedicated BI/SQL Serverno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
HTTP API
Supported programming languagesPython
R
Scala
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
any language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functions and aggregatesnouser defined functions and aggregates, HTTP Server extensions in Javano
Triggersnoyes infovia event handlersyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationMulti-source replication in HA-Clusternone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency in HA-ClusterImmediate Consistency
Foreign keys infoReferential integritynoyes inforelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
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.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and rolesno
More information provided by the system vendor
DatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022StardogYanza
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022StardogYanza
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