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DBMS > BigchainDB vs. Coveo vs. HEAVY.AI vs. Spark SQL

System Properties Comparison BigchainDB vs. Coveo vs. HEAVY.AI vs. Spark SQL

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Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonCoveo  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeSearch engineRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.79
Rank#212  Overall
#36  Document stores
Score2.28
Rank#114  Overall
#11  Search engines
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.bigchaindb.comwww.coveo.comgithub.com/­heavyai/­heavydb
www.heavy.ai
spark.apache.org/­sql
Technical documentationbigchaindb.readthedocs.io/­en/­latestdocs.coveo.comdocs.heavy.aispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCoveoHEAVY.AI, Inc.Apache Software Foundation
Initial release2016201220162014
Current release5.10, January 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoAGPL v3commercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonC++ and CUDAScala
Server operating systemsLinuxhostedLinuxLinux
OS X
Windows
Data schemeschema-freehybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nononono
Secondary indexesyesnono
SQL infoSupport of SQLnonoyesSQL-like DML and DDL statements
APIs and other access methodsCLI Client
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Thrift
Vega
JDBC
ODBC
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
C#
Java
JavaScript
Python
All languages supporting JDBC/ODBC/Thrift
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingyesSharding infoRound robinyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlyesgranular access controls, API key management, content filtersfine grained access rights according to SQL-standardno

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More resources
BigchainDBCoveoHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Spark SQL
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