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DBMS > Amazon DocumentDB vs. Google Cloud Bigtable vs. Microsoft Access vs. Netezza vs. XTDB

System Properties Comparison Amazon DocumentDB vs. Google Cloud Bigtable vs. Microsoft Access vs. Netezza vs. XTDB

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.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.)Data warehouse and analytics appliance part of IBM PureSystemsA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelDocument storeKey-value store
Wide column store
Relational DBMSRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score105.40
Rank#11  Overall
#8  Relational DBMS
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score0.09
Rank#351  Overall
#47  Document stores
Websiteaws.amazon.com/­documentdbcloud.google.com/­bigtablewww.microsoft.com/­en-us/­microsoft-365/­accesswww.ibm.com/­products/­netezzagithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­bigtable/­docsdeveloper.microsoft.com/­en-us/­accesswww.xtdb.com/­docs
DeveloperGoogleMicrosoftIBMJuxt Ltd.
Initial release20192015199220002019
Current release1902 (16.0.11328.20222), March 20191.19, September 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial infoBundled with Microsoft OfficecommercialOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Clojure
Server operating systemshostedhostedWindows infoNot a real database server, but making use of DLLsLinux infoincluded in applianceAll OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyesyes, extensible-data-notation format
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.nonono
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLnonoyes infobut not compliant to any SQL standardyeslimited SQL, making use of Apache Calcite
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
DAO
ODBC
OLE DB
JDBC
ODBC
OLE DB
HTTP REST
JDBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C
C++
Fortran
Java
Lua
Perl
Python
R
Clojure
Java
Server-side scripts infoStored proceduresnonoyes infosince Access 2010 using the ACE-engineyesno
Triggersnonoyes infosince Access 2010 using the ACE-enginenono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasInternal replication in Colossus, and regional replication between two clusters in different zonesnoneSource-replica replicationyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsAtomic single-row operationsACID infobut no files for transaction loggingACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users and rolesAccess 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 2003Users with fine-grained authorization concept

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More resources
Amazon DocumentDBGoogle Cloud BigtableMicrosoft AccessNetezza infoAlso called PureData System for Analytics by IBMXTDB infoformerly named Crux
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