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DBMS > Citus vs. Graphite vs. Microsoft Access vs. Spark SQL vs. YDB

System Properties Comparison Citus vs. Graphite vs. Microsoft Access vs. Spark SQL vs. YDB

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonGraphite  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSpark SQL  Xexclude from comparisonYDB  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLData 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.)Spark SQL is a component on top of 'Spark Core' for structured data processingA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMSDocument store
Relational 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
Score4.57
Rank#73  Overall
#5  Time Series DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websitewww.citusdata.comgithub.com/­graphite-project/­graphite-webwww.microsoft.com/­en-us/­microsoft-365/­accessspark.apache.org/­sqlgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationdocs.citusdata.comgraphite.readthedocs.iodeveloper.microsoft.com/­en-us/­accessspark.apache.org/­docs/­latest/­sql-programming-guide.htmlydb.tech/­en/­docs
DeveloperChris DavisMicrosoftApache Software FoundationYandex
Initial release20102006199220142019
Current release8.1, December 20181902 (16.0.11328.20222), March 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache 2.0commercial infoBundled with Microsoft OfficeOpen Source infoApache 2.0Open Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCPythonC++Scala
Server operating systemsLinuxLinux
Unix
Windows infoNot a real database server, but making use of DLLsLinux
OS X
Windows
Linux
Data schemeyesyesyesyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesNumeric data onlyyesyesyes
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 functionalitynonono
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoyes infobut not compliant to any SQL standardSQL-like DML and DDL statementsSQL-like query language (YQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Sockets
ADO.NET
DAO
ODBC
OLE DB
JDBC
ODBC
RESTful HTTP API (DynamoDB compatible)
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
JavaScript (Node.js)
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Java
Python
R
Scala
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes infosince Access 2010 using the ACE-enginenono
Triggersyesnoyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsnonenonenoneActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infobut no files for transaction loggingnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infolockingyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyesyes
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-standardnono infoa simple user-level security was built in till version Access 2003noAccess rights defined for Yandex Cloud users

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More resources
CitusGraphiteMicrosoft AccessSpark SQLYDB
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