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DBMS > Databricks vs. FatDB vs. Google Cloud Datastore vs. Microsoft Access vs. Warp 10

System Properties Comparison Databricks vs. FatDB vs. Google Cloud Datastore vs. Microsoft Access vs. Warp 10

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonWarp 10  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically 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.)TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Document storeRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websitewww.databricks.comcloud.google.com/­datastorewww.microsoft.com/­en-us/­microsoft-365/­accesswww.warp10.io
Technical documentationdocs.databricks.comcloud.google.com/­datastore/­docsdeveloper.microsoft.com/­en-us/­accesswww.warp10.io/­content/­02_Getting_started
DeveloperDatabricksFatCloudGoogleMicrosoftSenX
Initial release20132012200819922015
Current release1902 (16.0.11328.20222), March 2019
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infoBundled with Microsoft OfficeOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C++Java
Server operating systemshostedWindowshostedWindows infoNot a real database server, but making use of DLLsLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyesschema-free
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.yesnono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLwith Databricks SQLno infoVia inetgration in SQL ServerSQL-like query language (GQL)yes infobut not compliant to any SQL standardno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
HTTP API
Jupyter
WebSocket
Supported programming languagesPython
R
Scala
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infovia applicationsusing Google App Engineyes infosince Access 2010 using the ACE-engineyes infoWarpScript
Triggersyes infovia applicationsCallbacks using the Google Apps Engineyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorMulti-source replication using Paxosnoneselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
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.Immediate Consistency infobased on HBase
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.nonoyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess 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 2003Mandatory use of cryptographic tokens, containing fine-grained authorizations
More information provided by the system vendor
DatabricksFatDBGoogle Cloud DatastoreMicrosoft AccessWarp 10
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksFatDBGoogle Cloud DatastoreMicrosoft AccessWarp 10
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