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DBMS > Coveo vs. Databricks vs. HEAVY.AI

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

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Editorial information provided by DB-Engines
NameCoveo  Xexclude from comparisonDatabricks  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparison
DescriptionAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentThe 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 hardware
Primary database modelSearch engineDocument store
Relational DBMS
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.34
Rank#117  Overall
#11  Search engines
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score2.10
Rank#126  Overall
#61  Relational DBMS
Websitewww.coveo.comwww.databricks.comgithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationdocs.coveo.comdocs.databricks.comdocs.heavy.ai
DeveloperCoveoDatabricksHEAVY.AI, Inc.
Initial release201220132016
Current release5.10, January 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDA
Server operating systemshostedhostedLinux
Data schemehybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationFlexible Schema (defined schema, partial schema, schema free)yes
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.noyesno
Secondary indexesyesyesno
SQL infoSupport of SQLnowith Databricks SQLyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
Supported programming languagesC#
Java
JavaScript
Python
Python
R
Scala
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesno
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesyesSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDno
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.noyes
User concepts infoAccess controlgranular access controls, API key management, content filtersfine grained access rights according to SQL-standard
More information provided by the system vendor
CoveoDatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
CoveoDatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022
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