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DBMS > Coveo vs. Datomic vs. SiriDB vs. Spark SQL

System Properties Comparison Coveo vs. Datomic vs. SiriDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameCoveo  Xexclude from comparisonDatomic  Xexclude from comparisonSiriDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityOpen Source Time Series DBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelSearch engineRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.28
Rank#114  Overall
#11  Search engines
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.coveo.comwww.datomic.comsiridb.comspark.apache.org/­sql
Technical documentationdocs.coveo.comdocs.datomic.comdocs.siridb.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCoveoCognitectCesbitApache Software Foundation
Initial release2012201220172014
Current release1.0.6735, June 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoMIT LicenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureCScala
Server operating systemshostedAll OS with a Java VMLinuxLinux
OS X
Windows
Data schemehybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infoNumeric datayes
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 indexesyesyesyesno
SQL infoSupport of SQLnononoSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIRESTful HTTP APIHTTP APIJDBC
ODBC
Supported programming languagesC#
Java
JavaScript
Python
Clojure
Java
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsnono
TriggersyesBy using transaction functionsnono
Partitioning methods infoMethods for storing different data on different nodesyesnone infoBut extensive use of caching in the application peersShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone infoBut extensive use of caching in the application peersyesnone
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 integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesno
User concepts infoAccess controlgranular access controls, API key management, content filtersnosimple rights management via user accountsno

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More resources
CoveoDatomicSiriDBSpark SQL
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