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DBMS > Drizzle vs. Google BigQuery vs. LeanXcale vs. Microsoft Access vs. Microsoft Azure Table Storage

System Properties Comparison Drizzle vs. Google BigQuery vs. LeanXcale vs. Microsoft Access vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Large scale data warehouse service with append-only tablesA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesMicrosoft 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.)A Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Relational DBMSWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitecloud.google.com/­bigquerywww.leanxcale.comwww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationcloud.google.com/­bigquery/­docsdeveloper.microsoft.com/­en-us/­access
DeveloperDrizzle project, originally started by Brian AkerGoogleLeanXcaleMicrosoftMicrosoft
Initial release20082010201519922012
Current release7.2.4, September 20121902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialcommercial infoBundled with Microsoft Officecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemsFreeBSD
Linux
OS X
hostedWindows infoNot a real database server, but making use of DLLshosted
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesnoyesno
SQL infoSupport of SQLyes infowith proprietary extensionsyesyes infothrough Apache Derbyyes infobut not compliant to any SQL standardno
APIs and other access methodsJDBCRESTful HTTP/JSON APIJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
ADO.NET
DAO
ODBC
OLE DB
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C
Java
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions infoin JavaScriptyes infosince Access 2010 using the ACE-engineno
Triggersno infohooks for callbacks inside the server can be used.noyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoSince BigQuery is designed for querying dataACIDACID infobut no files for transaction loggingoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.noyesno
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)no infoa simple user-level security was built in till version Access 2003Access rights based on private key authentication or shared access signatures

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More resources
DrizzleGoogle BigQueryLeanXcaleMicrosoft AccessMicrosoft Azure Table Storage
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