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DBMS > Google Cloud Datastore vs. IBM Db2 Event Store vs. Microsoft Access vs. Postgres-XL

System Properties Comparison Google Cloud Datastore vs. IBM Db2 Event Store vs. Microsoft Access vs. Postgres-XL

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed Event Store optimized for Internet of Things use casesMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument storeEvent Store
Time Series DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websitecloud.google.com/­datastorewww.ibm.com/­products/­db2-event-storewww.microsoft.com/­en-us/­microsoft-365/­accesswww.postgres-xl.org
Technical documentationcloud.google.com/­datastore/­docswww.ibm.com/­docs/­en/­db2-event-storedeveloper.microsoft.com/­en-us/­accesswww.postgres-xl.org/­documentation
DeveloperGoogleIBMMicrosoft
Initial release2008201719922014 infosince 2012, originally named StormDB
Current release2.01902 (16.0.11328.20222), March 201910 R1, October 2018
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availablecommercial infoBundled with Microsoft OfficeOpen Source infoMozilla public license
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 and C++C++C
Server operating systemshostedLinux infoLinux, macOS, Windows for the developer additionWindows infoNot a real database server, but making use of DLLsLinux
macOS
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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.nonoyes infoXML type, but no XML query functionality
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)yes infothrough the embedded Spark runtimeyes infobut not compliant to any SQL standardyes infodistributed, parallel query execution
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresusing Google App Engineyesyes infosince Access 2010 using the ACE-engineuser defined functions
TriggersCallbacks using the Google Apps Enginenoyes infosince Access 2010 using the ACE-engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosActive-active shard replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infobut no files for transaction loggingACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes infobut no files for transaction loggingyes
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-standardno infoa simple user-level security was built in till version Access 2003fine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreIBM Db2 Event StoreMicrosoft AccessPostgres-XL
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