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DBMS > Apache Druid vs. Coveo vs. Microsoft Azure Table Storage vs. TerminusDB

System Properties Comparison Apache Druid vs. Coveo vs. Microsoft Azure Table Storage vs. TerminusDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonCoveo  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentA Wide Column Store for rapid development using massive semi-structured datasetsScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships
Primary database modelRelational DBMS
Time Series DBMS
Search engineWide column storeGraph DBMS
Secondary database modelsDocument store
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.85
Rank#96  Overall
#50  Relational DBMS
#6  Time Series DBMS
Score2.14
Rank#116  Overall
#11  Search engines
Score3.55
Rank#80  Overall
#6  Wide column stores
Score0.19
Rank#311  Overall
#27  Graph DBMS
Websitedruid.apache.orgwww.coveo.comazure.microsoft.com/­en-us/­services/­storage/­tablesterminusdb.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.coveo.comterminusdb.github.io/­terminusdb/­#
DeveloperApache Software Foundation and contributorsCoveoMicrosoftDataChemist Ltd.
Initial release2012201220122018
Current release30.0.0, June 202411.0.0, January 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaProlog, Rust
Server operating systemsLinux
OS X
Unix
hostedhostedLinux
Data schemeyes infoschema-less columns are supportedhybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesno
SQL infoSupport of SQLSQL for queryingnonoSQL-like query language (WOQL)
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP APIRESTful HTTP APIOWL
RESTful HTTP API
WOQL (Web Object Query Language)
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
Java
JavaScript
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript
Python
Server-side scripts infoStored proceduresnononoyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedyesSharding infoImplicit feature of the cloud serviceGraph Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Journaling Streams
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory journaling
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemgranular access controls, API key management, content filtersAccess rights based on private key authentication or shared access signaturesRole-based access control

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More resources
Apache DruidCoveoMicrosoft Azure Table StorageTerminusDB infoformer name was DataChemist
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