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DBMS > Citus vs. Elasticsearch vs. Google Cloud Bigtable vs. Kyligence Enterprise

System Properties Comparison Citus vs. Elasticsearch vs. Google Cloud Bigtable vs. Kyligence Enterprise

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonElasticsearch  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKyligence Enterprise  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A distributed analytics engine for big data, built on top of Apache Kylin
Primary database modelRelational DBMSSearch engineKey-value store
Wide column store
Relational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score132.83
Rank#7  Overall
#1  Search engines
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.46
Rank#266  Overall
#124  Relational DBMS
Websitewww.citusdata.comwww.elastic.co/­elasticsearchcloud.google.com/­bigtablekyligence.io/­kyligence-enterprise
Technical documentationdocs.citusdata.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlcloud.google.com/­bigtable/­docs
DeveloperElasticGoogleKyligence, Inc.
Initial release2010201020152016
Current release8.1, December 20188.6, January 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoElastic Licensecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaJava
Server operating systemsLinuxAll OS with a Java VMhostedLinux
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.yes infospecific XML type available, but no XML query functionalitynonono
Secondary indexesyesyes infoAll search fields are automatically indexednoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL-like query languagenoANSI SQL for queries (using Apache Calcite)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yesno
Triggersyesyes infoby using the 'percolation' featureno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyesInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop Connectoryesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic single-row operations
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.noMemcached and Redis integrationnono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
CitusElasticsearchGoogle Cloud BigtableKyligence Enterprise
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