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DBMS > Google Cloud Datastore vs. InfinityDB vs. OpenMLDB vs. Riak KV

System Properties Comparison Google Cloud Datastore vs. InfinityDB vs. OpenMLDB vs. Riak KV

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonInfinityDB  Xexclude from comparisonOpenMLDB  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Java embedded Key-Value Store which extends the Java Map interfaceAn open-source machine learning database that provides a feature platform for training and inferenceDistributed, fault tolerant key-value store
Primary database modelDocument storeKey-value storeTime Series DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.08
Rank#365  Overall
#55  Key-value stores
Score0.10
Rank#359  Overall
#36  Time Series DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Websitecloud.google.com/­datastoreboilerbay.comopenmldb.ai
Technical documentationcloud.google.com/­datastore/­docsboilerbay.com/­infinitydb/­manualopenmldb.ai/­docs/­zh/­mainwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperGoogleBoiler Bay Inc.4 Paradigm Inc.OpenSource, formerly Basho Technologies
Initial release2008200220202009
Current release4.02024-2 February 20243.2.0, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Java, ScalaErlang
Server operating systemshostedAll OS with a Java VMLinuxLinux
OS X
Data schemeschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeFixed schemaschema-free
Typing infopredefined data types such as float or dateyes, details hereyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesno
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.nononono
Secondary indexesyesno infomanual creation possible, using inversions based on multi-value capabilityyesrestricted
SQL infoSupport of SQLSQL-like query language (GQL)noyesno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
SQLAlchemy
HTTP API
Native Erlang Interface
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaC++
Go
Java
Python
Scala
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
Server-side scripts infoStored proceduresusing Google App EnginenonoErlang
TriggersCallbacks using the Google Apps Enginenonoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioningSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosnoneSource-replica replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyes
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 Consistency infoREAD-COMMITTED or SERIALIZEDImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsno infomanual creation possible, using inversions based on multi-value capabilitynono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoOptimistic locking for transactions; no isolation for bulk loadsnono
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.nonoyes
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-standardyes, using Riak Security

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More resources
Google Cloud DatastoreInfinityDBOpenMLDBRiak KV
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