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DBMS > EsgynDB vs. Google Cloud Bigtable vs. Kingbase vs. TimescaleDB

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. Kingbase vs. TimescaleDB

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKingbase  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score0.44
Rank#258  Overall
#117  Relational DBMS
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablewww.kingbase.com.cnwww.timescale.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.timescale.com
DeveloperEsgynGoogleBeiJing KINGBASE Information technologies inc.Timescale
Initial release2015201519992017
Current releaseV8.0, August 20212.15.0, May 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen 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 languageC++, JavaC and JavaC
Server operating systemsLinuxhostedLinux
Windows
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.nonoyesyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyesnoStandard with numerous extensionsyes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresJava Stored Proceduresnouser defined functionsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning (by range, list and hash) and vertical partitioningyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesyesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
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.nonono
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)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
EsgynDBGoogle Cloud BigtableKingbaseTimescaleDB
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