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DBMS > DolphinDB vs. Google BigQuery vs. Microsoft Access vs. Microsoft Azure Cosmos DB

System Properties Comparison DolphinDB vs. Google BigQuery vs. Microsoft Access vs. Microsoft Azure Cosmos DB

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Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparison
DescriptionTime Series DBMS for big data, integrated with a lightweight distributed computing framework and a vector programming languageLarge scale data warehouse service with append-only tablesMicrosoft 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.)Globally distributed, horizontally scalable, multi-model database service
Primary database modelTime Series DBMSRelational DBMSRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.39
Rank#225  Overall
#13  Time Series DBMS
Score27.59
Rank#26  Overall
#15  Relational DBMS
Score119.90
Rank#10  Overall
#7  Relational DBMS
Score30.68
Rank#24  Overall
#3  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Websitewww.dolphindb.comcloud.google.com/­bigqueryproducts.office.com/­en-us/­accessazure.microsoft.com/­services/­cosmos-db
Technical documentationwww.dolphindb.com/­helpcloud.google.com/­bigquery/­docsmsdn.microsoft.com/­en-us/­library/­office/­ff604965.aspxdocs.microsoft.com/­en-us/­azure/­cosmos-db
DeveloperDolphinDB, IncGoogleMicrosoftMicrosoft
Initial release2018201019922014
Current release1902 (16.0.11328.20222), March 2019
License infoCommercial or Open Sourcecommercial infofree community version availablecommercialcommercial infoBundled with Microsoft Officecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemsLinux
Windows
hostedWindows infoNot a real database server, but making use of DLLshosted
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infoJSON types
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 indexesnonoyesyes infoAll properties auto-indexed by default
SQL infoSupport of SQLSQL-like query languageyesyes infobut not compliant to any SQL standardSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP/JSON APIADO.NET
DAO
ODBC
OLE DB
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Supported programming languagesC#
C++
Java
JavaScript
Python
R
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
Server-side scripts infoStored proceduresyesuser defined functions infoin JavaScriptyes infosince Access 2010 using the ACE-engineJavaScript
Triggersnonoyes infosince Access 2010 using the ACE-engineJavaScript
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnonenoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesno infoSince BigQuery is designed for querying dataACID infobut no files for transaction loggingMulti-item ACID transactions with snapshot isolation within a partition
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes 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 controlAdministrators, Users, GroupsAccess privileges (owner, writer, reader) for whole datasets, not for individual tables infoGoogle Cloud Identity & Access Management (IAM)no infoa simple user-level security was built in till version Access 2003Access rights can be defined down to the item level

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More resources
DolphinDBGoogle BigQueryMicrosoft AccessMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB
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