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DBMS > Citus vs. Databricks vs. Google BigQuery vs. Graphite vs. Microsoft Access

System Properties Comparison Citus vs. Databricks vs. Google BigQuery vs. Graphite vs. Microsoft Access

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonDatabricks  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonGraphite  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLThe 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.Large scale data warehouse service with append-only tablesData logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperMicrosoft 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 store
Relational DBMS
Relational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score4.57
Rank#73  Overall
#5  Time Series DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Websitewww.citusdata.comwww.databricks.comcloud.google.com/­bigquerygithub.com/­graphite-project/­graphite-webwww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationdocs.citusdata.comdocs.databricks.comcloud.google.com/­bigquery/­docsgraphite.readthedocs.iodeveloper.microsoft.com/­en-us/­access
DeveloperDatabricksGoogleChris DavisMicrosoft
Initial release20102013201020061992
Current release8.1, December 20181902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercialOpen Source infoApache 2.0commercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCPythonC++
Server operating systemsLinuxhostedhostedLinux
Unix
Windows infoNot a real database server, but making use of DLLs
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyesNumeric data onlyyes
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 infospecific XML type available, but no XML query functionalityyesnono
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionswith Databricks SQLyesnoyes infobut not compliant to any SQL standard
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
RESTful HTTP/JSON APIHTTP API
Sockets
ADO.NET
DAO
ODBC
OLE DB
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Python
R
Scala
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
JavaScript (Node.js)
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functions and aggregatesuser defined functions infoin JavaScriptnoyes infosince Access 2010 using the ACE-engine
Triggersyesnonoyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesShardingnonenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistencynone
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno infoSince BigQuery is designed for querying datanoACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infolockingyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)nono infoa simple user-level security was built in till version Access 2003
More information provided by the system vendor
CitusDatabricksGoogle BigQueryGraphiteMicrosoft Access
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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