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DBMS > EsgynDB vs. Google Cloud Bigtable vs. Riak KV vs. TimescaleDB vs. Ultipa

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. Riak KV vs. TimescaleDB vs. Ultipa

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonRiak KV  Xexclude from comparisonTimescaleDB  Xexclude from comparisonUltipa  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.Distributed, fault tolerant key-value storeA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLHigh performance Graph DBMS supporting HTAP high availability cluster deployment
Primary database modelRelational DBMSKey-value store
Wide column store
Key-value store infowith links between data sets and object tags for the creation of secondary indexesTime Series DBMSGraph DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score4.01
Rank#79  Overall
#9  Key-value stores
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score0.19
Rank#330  Overall
#30  Graph DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablewww.timescale.comwww.ultipa.com
Technical documentationcloud.google.com/­bigtable/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latestdocs.timescale.comwww.ultipa.com/­document
DeveloperEsgynGoogleOpenSource, formerly Basho TechnologiesTimescaleUltipa
Initial release20152015200920172019
Current release3.2.0, December 20222.15.0, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaErlangC
Server operating systemsLinuxhostedLinux
OS X
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnononumerics, 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.nononoyes
Secondary indexesyesnorestrictedyes
SQL infoSupport of SQLyesnonoyes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
Native Erlang Interface
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresJava Stored ProceduresnoErlanguser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonoyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infono "single point of failure"yes, 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 zonesselectable replication factorSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyesno
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 integrityyesnono infolinks between data sets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACID
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)yes, using Riak Securityfine grained access rights according to SQL-standard

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More resources
EsgynDBGoogle Cloud BigtableRiak KVTimescaleDBUltipa
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