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DBMS > FileMaker vs. Google Cloud Datastore vs. LevelDB vs. Microsoft Access vs. VelocityDB

System Properties Comparison FileMaker vs. Google Cloud Datastore vs. LevelDB vs. Microsoft Access vs. VelocityDB

Editorial information provided by DB-Engines
NameFileMaker  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonVelocityDB  Xexclude from comparison
DescriptionFileMaker is a cross-platform RDBMS that includes a GUI frontend.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesMicrosoft 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.)A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelRelational DBMSDocument storeKey-value storeRelational DBMSGraph DBMS
Object oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score49.73
Rank#20  Overall
#14  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score2.75
Rank#107  Overall
#19  Key-value stores
Score105.40
Rank#11  Overall
#8  Relational DBMS
Score0.11
Rank#347  Overall
#35  Graph DBMS
#15  Object oriented DBMS
Websitewww.claris.com/­filemakercloud.google.com/­datastoregithub.com/­google/­leveldbwww.microsoft.com/­en-us/­microsoft-365/­accessvelocitydb.com
Technical documentationwww.claris.com/­resources/­documentationcloud.google.com/­datastore/­docsgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddeveloper.microsoft.com/­en-us/­accessvelocitydb.com/­UserGuide
DeveloperClaris infoa subsidiary of AppleGoogleGoogleMicrosoftVelocityDB Inc
Initial release19832008201119922011
Current release19.4.1, November 20211.23, February 20211902 (16.0.11328.20222), March 20197.x
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSDcommercial infoBundled with Microsoft Officecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C#
Server operating systemsiOS infoclient part only
Linux
OS X
Windows
hostedIllumos
Linux
OS X
Windows
Windows infoNot a real database server, but making use of DLLsAny that supports .NET
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details herenoyesyes
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.yes infoA http query request can return the data in XML formatnonono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLyes infovia pluginsSQL-like query language (GQL)noyes infobut not compliant to any SQL standardno
APIs and other access methodsFilemaker WebDirect
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
.Net
Supported programming languagesPHP.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
Server-side scripts infoStored proceduresyesusing Google App Enginenoyes infosince Access 2010 using the ACE-engineno
TriggersyesCallbacks using the Google Apps Enginenoyes infosince Access 2010 using the ACE-engineCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication, warm standby infosince Version 14Multi-source replication using Paxosnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes 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.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infobut no files for transaction loggingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes 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.noyes
User concepts infoAccess controlsimple rights management via user accounts and connection to external directory servicesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono infoa simple user-level security was built in till version Access 2003Based on Windows Authentication

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More resources
FileMakerGoogle Cloud DatastoreLevelDBMicrosoft AccessVelocityDB
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