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DBMS > Google Cloud Datastore vs. Oracle Berkeley DB vs. ReductStore vs. Splice Machine

System Properties Comparison Google Cloud Datastore vs. Oracle Berkeley DB vs. ReductStore vs. Splice Machine

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonReductStore  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWidely used in-process key-value storeDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Time Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#71  Overall
#12  Document stores
Score1.88
Rank#130  Overall
#23  Key-value stores
#3  Native XML DBMS
Score0.00
Rank#385  Overall
#40  Time Series DBMS
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websitecloud.google.com/­datastorewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlgithub.com/­reductstore
www.reduct.store
splicemachine.com
Technical documentationcloud.google.com/­datastore/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlwww.reduct.store/­docssplicemachine.com/­how-it-works
DeveloperGoogleOracle infooriginally developed by Sleepycat, which was acquired by OracleReductStore LLCSplice Machine
Initial release2008199420232014
Current release18.1.40, May 20201.9, March 20243.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infocommercial license availableOpen Source infoBusiness Source License 1.1Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, Java, C++ (depending on the Berkeley DB edition)C++, RustJava
Server operating systemshostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Docker
Linux
macOS
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyes
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.noyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)yes infoSQL interfaced based on SQLite is availableyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C++
JavaScript (Node.js)
Python
Rust
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresusing Google App Enginenoyes infoJava
TriggersCallbacks using the Google Apps Engineyes infoonly for the SQL APIyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud DataflownoYes, via Full Spark Integration
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
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users, groups and roles according to SQL-standard

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More resources
Google Cloud DatastoreOracle Berkeley DBReductStoreSplice Machine
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