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

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

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Editorial information provided by DB-Engines
NameGalaxybase  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInfinityDB  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionScalable, ACID-compliant native distributed parallel graph platformAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Java embedded Key-Value Store which extends the Java Map interfaceDistributed, fault tolerant key-value store
Primary database modelGraph DBMSDocument storeKey-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
Score0.00
Rank#385  Overall
#40  Graph DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score0.00
Rank#383  Overall
#59  Key-value stores
Score3.84
Rank#76  Overall
#9  Key-value stores
Websitegalaxybase.comcloud.google.com/­datastoreboilerbay.com
Technical documentationcloud.google.com/­datastore/­docsboilerbay.com/­infinitydb/­manualwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperChuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司GoogleBoiler Bay Inc.OpenSource, formerly Basho Technologies
Initial release2017200820022009
Current releaseNov 20, November 20214.03.2.0, December 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and JavaJavaErlang
Server operating systemsLinuxhostedAll OS with a Java VMLinux
OS X
Data schemeStrong typed schemaschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyes 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 SQLnoSQL-like query language (GQL)nono
APIs and other access methodsBrowser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API
gRPC (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)
HTTP API
Native Erlang Interface
Supported programming languagesGo
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
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 proceduresuser defined procedures and functionsusing Google App EnginenoErlang
TriggersCallbacks using the Google Apps Enginenoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosnoneselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 infoREAD-COMMITTED or SERIALIZEDEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infovia ReferenceProperties or Ancestor pathsno 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 dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID 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.yesnono
User concepts infoAccess controlRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyes, using Riak Security

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More resources
GalaxybaseGoogle Cloud DatastoreInfinityDBRiak KV
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