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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  Xexclude from comparisonInfinityDB  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMultithreaded, transactional RDBMS written in Java infoalso known as HSQLDBA Java embedded Key-Value Store which extends the Java Map interfaceDistributed, fault tolerant key-value store
Primary database modelDocument storeRelational DBMSKey-value storeKey-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score3.23
Rank#93  Overall
#48  Relational DBMS
Score0.08
Rank#365  Overall
#55  Key-value stores
Score4.01
Rank#79  Overall
#9  Key-value stores
Websitecloud.google.com/­datastorehsqldb.orgboilerbay.com
Technical documentationcloud.google.com/­datastore/­docshsqldb.org/­web/­hsqlDocsFrame.htmlboilerbay.com/­infinitydb/­manualwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperGoogleBoiler Bay Inc.OpenSource, formerly Basho Technologies
Initial release2008200120022009
Current release2.7.2, June 20234.03.2.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infobased on BSD licensecommercialOpen 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 languageJavaJavaErlang
Server operating systemshostedAll OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modesAll OS with a Java VMLinux
OS X
Data schemeschema-freeyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysno
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 indexesyesyesno infomanual creation possible, using inversions based on multi-value capabilityrestricted
SQL infoSupport of SQLSQL-like query language (GQL)yesnono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API infoJDBC via HTTP
JDBC
ODBC
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP API
Native Erlang Interface
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC
Java
JavaC 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 EngineJava, SQLnoErlang
TriggersCallbacks using the Google Apps Engineyesnoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosnonenoneselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonoyes
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 infoREAD-COMMITTED or SERIALIZEDEventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesno infomanual creation possible, using inversions based on multi-value capabilityno 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 TransactionsACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsno
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardnoyes, using Riak Security

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More resources
Google Cloud DatastoreHyperSQL infoalso known as HSQLDBInfinityDBRiak KV
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