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DBMS > CrateDB vs. Google Cloud Datastore vs. Microsoft Access vs. SQL.JS

System Properties Comparison CrateDB vs. Google Cloud Datastore vs. Microsoft Access vs. SQL.JS

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSQL.JS  Xexclude from comparison
DescriptionDistributed Database based on LuceneAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMicrosoft 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.)Port of SQLite to JavaScript
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Document storeRelational DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.69
Rank#226  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#11  Vector DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score93.76
Rank#12  Overall
#8  Relational DBMS
Score0.53
Rank#246  Overall
#115  Relational DBMS
Websitecratedb.comcloud.google.com/­datastorewww.microsoft.com/­en-us/­microsoft-365/­accesssql.js.org
Technical documentationcratedb.com/­docscloud.google.com/­datastore/­docsdeveloper.microsoft.com/­en-us/­accesssql.js.org/­documentation/­index.html
DeveloperCrateGoogleMicrosoftAlon Zakai infoenhancements implemented by others
Initial release2013200819922012
Current release5.8.1, August 20241902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Sourcecommercialcommercial infoBundled with Microsoft OfficeOpen Source
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 languageJavaC++JavaScript
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedWindows infoNot a real database server, but making use of DLLsserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.nonono
Secondary indexesyesyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like query language (GQL)yes infobut not compliant to any SQL standardyes infoSQL-92 is not fully supported
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
JavaScript API
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
JavaScript
Server-side scripts infoStored proceduresuser defined functions (Javascript)using Google App Engineyes infosince Access 2010 using the ACE-engineno
TriggersnoCallbacks using the Google Apps Engineyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelMulti-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 systemEventual Consistency
Read-after-write consistency on record level
Immediate 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.none
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infobut no files for transaction loggingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingno infoexcept by serializing a db to a file
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlrights management via user accountsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no infoa simple user-level security was built in till version Access 2003no

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More resources
CrateDBGoogle Cloud DatastoreMicrosoft AccessSQL.JS
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