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DBMS > Drizzle vs. Google Cloud Datastore vs. InfinityDB vs. Microsoft Access

System Properties Comparison Drizzle vs. Google Cloud Datastore vs. InfinityDB vs. Microsoft Access

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInfinityDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Java embedded Key-Value Store which extends the Java Map interfaceMicrosoft 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.)
Primary database modelRelational DBMSDocument storeKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#71  Overall
#12  Document stores
Score0.00
Rank#383  Overall
#59  Key-value stores
Score93.76
Rank#12  Overall
#8  Relational DBMS
Websitecloud.google.com/­datastoreboilerbay.comwww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationcloud.google.com/­datastore/­docsboilerbay.com/­infinitydb/­manualdeveloper.microsoft.com/­en-us/­access
DeveloperDrizzle project, originally started by Brian AkerGoogleBoiler Bay Inc.Microsoft
Initial release2008200820021992
Current release7.2.4, September 20124.01902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialcommercial infoBundled with Microsoft Office
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++JavaC++
Server operating systemsFreeBSD
Linux
OS X
hostedAll OS with a Java VMWindows infoNot a real database server, but making use of DLLs
Data schemeyesschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes
Typing infopredefined data types such as float or dateyesyes, details hereyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes
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.nono
Secondary indexesyesyesno infomanual creation possible, using inversions based on multi-value capabilityyes
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like query language (GQL)noyes infobut not compliant to any SQL standard
APIs and other access methodsJDBCgRPC (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)
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesC
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresnousing Google App Enginenoyes infosince Access 2010 using the ACE-engine
Triggersno infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Enginenoyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
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 infoREAD-COMMITTED or SERIALIZED
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsno infomanual creation possible, using inversions based on multi-value capabilityyes
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 loadsACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess 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 2003

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More resources
DrizzleGoogle Cloud DatastoreInfinityDBMicrosoft Access
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