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DBMS > Datastax Enterprise vs. Microsoft Access vs. Spark SQL

System Properties Comparison Datastax Enterprise vs. Microsoft Access vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatastax Enterprise  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.Microsoft 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 processing
Primary database modelWide column storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.90
Rank#43  Overall
#4  Wide column stores
Score141.01
Rank#9  Overall
#6  Relational DBMS
Score16.72
Rank#35  Overall
#21  Relational DBMS
Websitewww.datastax.com/­products/­datastax-enterpriseproducts.office.com/­en-us/­accessspark.apache.org/­sql
Technical documentationdocs.datastax.commsdn.microsoft.com/­en-us/­library/­office/­ff604965.aspxspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDataStaxMicrosoftApache Software Foundation
Initial release201119922014
Current release6.7, December 20181902 (16.0.11328.20222), March 2019v2.4.3, May 2019
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft OfficeOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Scala
Server operating systemsLinux
OS X
Windows infoNot a real database server, but making use of DLLsLinux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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
SQL infoSupport of SQLSQL-like DML and DDL statements (CQL); Spark SQLyes infobut not compliant to any SQL standardSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
DAO
OLE DB
ADO.NET
ODBC
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infosince Access 2010 using the ACE-engineno
Triggersyesyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"noneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter aware, advanced replication for edge computingnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency infoconsistency level can be individually decided with each write operation
Immediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes 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.yesno
User concepts infoAccess controlAccess rights for users can be defined per objectno infoa simple user-level security was built in till version Access 2003no
More information provided by the system vendor
Datastax EnterpriseMicrosoft AccessSpark SQL
Specific characteristics100% continuous availability, real-time, distributed, massive scale data management...
» more
Competitive advantagesSupporting the following application requirements: Contextual: complete data layer...
» more
Typical application scenariosApplications that must serve contextual information and be always-on, distributed,...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald’s, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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More resources
Datastax EnterpriseMicrosoft AccessSpark SQL
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Conferences and events

Spark Summit Europe 2019
Amsterdam, Netherlands, 15-17 October 2019

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