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DBMS > Google Cloud Datastore vs. Hypertable vs. OpenMLDB

System Properties Comparison Google Cloud Datastore vs. Hypertable vs. OpenMLDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHypertable  Xexclude from comparisonOpenMLDB  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn open source BigTable implementation based on distributed file systems such as HadoopAn open-source machine learning database that provides a feature platform for training and inference
Primary database modelDocument storeWide column storeTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.02
Rank#367  Overall
#37  Time Series DBMS
Websitecloud.google.com/­datastoreopenmldb.ai
Technical documentationcloud.google.com/­datastore/­docsopenmldb.ai/­docs/­zh/­main
DeveloperGoogleHypertable Inc.4 Paradigm Inc.
Initial release200820092020
Current release0.9.8.11, March 20162024-2 February 2024
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availableOpen Source
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++, Java, Scala
Server operating systemshostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux
Data schemeschema-freeschema-freeFixed schema
Typing infopredefined data types such as float or dateyes, details herenoyes
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.nono
Secondary indexesyesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLSQL-like query language (GQL)noyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
C++ API
Thrift
JDBC
SQLAlchemy
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
C++
Go
Java
Python
Scala
Server-side scripts infoStored proceduresusing Google App Enginenono
TriggersCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor on file system levelSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreHypertableOpenMLDB
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