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DBMS > Google BigQuery vs. Microsoft Access vs. QuestDB

System Properties Comparison Google BigQuery vs. Microsoft Access vs. QuestDB

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionLarge 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.)A high performance open source SQL database for time series data
Primary database modelRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.90
Rank#19  Overall
#13  Relational DBMS
Score105.40
Rank#11  Overall
#8  Relational DBMS
Score2.48
Rank#115  Overall
#9  Time Series DBMS
Websitecloud.google.com/­bigquerywww.microsoft.com/­en-us/­microsoft-365/­accessquestdb.io
Technical documentationcloud.google.com/­bigquery/­docsdeveloper.microsoft.com/­en-us/­accessquestdb.io/­docs
DeveloperGoogleMicrosoftQuestDB Technology Inc
Initial release201019922014
Current release1902 (16.0.11328.20222), March 2019
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft OfficeOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java (Zero-GC), C++, Rust
Server operating systemshostedWindows infoNot a real database server, but making use of DLLsLinux
macOS
Windows
Data schemeyesyesyes infoschema-free via InfluxDB Line Protocol
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 indexesnoyesno
SQL infoSupport of SQLyesyes infobut not compliant to any SQL standardSQL with time-series extensions
APIs and other access methodsRESTful HTTP/JSON APIADO.NET
DAO
ODBC
OLE DB
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptyes infosince Access 2010 using the ACE-engineno
Triggersnoyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesnonenonehorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACID infobut no files for transaction loggingACID for single-table writes
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.noyes infothrough memory mapped files
User concepts infoAccess controlAccess 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 2003
More information provided by the system vendor
Google BigQueryMicrosoft AccessQuestDB
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
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