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DBMS > Citus vs. Google Cloud Bigtable vs. HugeGraph vs. TimescaleDB

System Properties Comparison Citus vs. Google Cloud Bigtable vs. HugeGraph vs. TimescaleDB

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHugeGraph  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A fast-speed and highly-scalable Graph DBMSA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSKey-value store
Wide column store
Graph DBMSTime Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.citusdata.comcloud.google.com/­bigtablegithub.com/­hugegraph
hugegraph.apache.org
www.timescale.com
Technical documentationdocs.citusdata.comcloud.google.com/­bigtable/­docshugegraph.apache.org/­docsdocs.timescale.com
DeveloperGoogleBaiduTimescale
Initial release2010201520182017
Current release8.1, December 20180.92.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaC
Server operating systemsLinuxhostedLinux
macOS
Unix
Linux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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 functionalitynonoyes
Secondary indexesyesnoyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnonoyes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
TinkerPop Gremlin
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
Groovy
Java
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noasynchronous Gremlin script jobsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsInternal replication in Colossus, and regional replication between two clusters in different zonesyes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDACID
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.nonoyesno
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)Users, roles and permissionsfine grained access rights according to SQL-standard

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More resources
CitusGoogle Cloud BigtableHugeGraphTimescaleDB
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