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DBMS > Google Cloud Bigtable vs. MarkLogic vs. Microsoft Access vs. Microsoft Azure Synapse Analytics vs. Spark SQL

System Properties Comparison Google Cloud Bigtable vs. MarkLogic vs. Microsoft Access vs. Microsoft Azure Synapse Analytics vs. Spark SQL

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Operational and transactional Enterprise NoSQL databaseMicrosoft 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.)Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value store
Wide column store
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitecloud.google.com/­bigtablewww.marklogic.comwww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­services/­synapse-analyticsspark.apache.org/­sql
Technical documentationcloud.google.com/­bigtable/­docsdocs.marklogic.comdeveloper.microsoft.com/­en-us/­accessdocs.microsoft.com/­azure/­synapse-analyticsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleMarkLogic Corp.MicrosoftMicrosoftApache Software Foundation
Initial release20152001199220162014
Current release11.0, December 20221902 (16.0.11328.20222), March 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availablecommercial infoBundled with Microsoft OfficecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C++Scala
Server operating systemshostedLinux
OS X
Windows
Windows infoNot a real database server, but making use of DLLshostedLinux
OS X
Windows
Data schemeschema-freeschema-free infoSchema can be enforcedyesyesyes
Typing infopredefined data types such as float or datenoyesyesyesyes
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.noyesnono
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLnoyes infoSQL92yes infobut not compliant to any SQL standardyesSQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
Java
PHP
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia XQuery or JavaScriptyes infosince Access 2010 using the ACE-engineTransact SQLno
Triggersnoyesyes infosince Access 2010 using the ACE-enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding, horizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyesnoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID infocan act as a resource manager in an XA/JTA transactionACID infobut no files for transaction loggingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.noyes, with Range Indexesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control at the document and subdocument levelsno infoa simple user-level security was built in till version Access 2003yesno

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More resources
Google Cloud BigtableMarkLogicMicrosoft AccessMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSpark SQL
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