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DBMS > Apache Kylin vs. DataFS vs. Google Cloud Datastore vs. TimescaleDB

System Properties Comparison Apache Kylin vs. DataFS vs. Google Cloud Datastore vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonDataFS  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSObject oriented DBMSDocument storeTime Series DBMS
Secondary database modelsGraph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score0.09
Rank#360  Overall
#17  Object oriented DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitekylin.apache.orgnewdatabase.comcloud.google.com/­datastorewww.timescale.com
Technical documentationkylin.apache.org/­docsdev.mobiland.com/­Overview.xspcloud.google.com/­datastore/­docsdocs.timescale.com
DeveloperApache Software Foundation, originally contributed from eBay IncMobiland AGGoogleTimescale
Initial release2015201820082017
Current release3.1.0, July 20201.1.263, October 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0
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 languageJavaC
Server operating systemsLinuxWindowshostedLinux
OS X
Windows
Data schemeyesClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details herenumerics, 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 indexesyesnoyesyes
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)noSQL-like query language (GQL)yes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
Proprietary client DLL
WinRT client
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C#
C++
VB.Net
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresusing Google App Engineuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersno, except callback-events from server when changes happenedCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
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.nononono
User concepts infoAccess controlWindows-ProfileAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Apache KylinDataFSGoogle Cloud DatastoreTimescaleDB
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