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DBMS > Google BigQuery vs. GridGain vs. Quasardb vs. TimescaleDB

System Properties Comparison Google BigQuery vs. GridGain vs. Quasardb vs. TimescaleDB

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonGridGain  Xexclude from comparisonQuasardb  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesGridGain is an in-memory computing platform, built on Apache IgniteDistributed, high-performance timeseries databaseA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSKey-value store
Relational DBMS
Time Series DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score55.69
Rank#21  Overall
#14  Relational DBMS
Score2.38
Rank#124  Overall
#24  Key-value stores
#61  Relational DBMS
Score0.23
Rank#315  Overall
#25  Time Series DBMS
Score4.76
Rank#82  Overall
#5  Time Series DBMS
Websitecloud.google.com/­bigquerywww.gridgain.comquasardb.netwww.timescale.com
Technical documentationcloud.google.com/­bigquery/­docswww.gridgain.com/­docs/­latestdoc.quasar.ai/­masterdocs.timescale.com
DeveloperGoogleGridGain Systems, Inc.quasardbTimescale
Initial release2010200720092017
Current releaseGridGain 8.5.13.13.3, April 20222.6.0, February 2022
License infoCommercial or Open Sourcecommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetC++C
Server operating systemshostedLinux
OS X
Solaris
Windows
BSD
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infointeger and binarynumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data 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.noyesnoyes
Secondary indexesnoyesyes infowith tagsyes
SQL infoSupport of SQLyesANSI-99 for query and DML statements, subset of DDLSQL-like query languageyes infofull PostgreSQL SQL syntax
APIs and other access methodsRESTful HTTP/JSON APIHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptyes (compute grid and cache interceptors can be used instead)nouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyes (cache interceptors and events)noyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoconsistent hashingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Source-replica replication with selectable replication factorSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)with Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoTransient modeno
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Security Hooks for custom implementationsCryptographically strong user authentication and audit trailfine grained access rights according to SQL-standard
More information provided by the system vendor
Google BigQueryGridGainQuasardbTimescaleDB
Specific characteristicsTimescale is the creator of TimescaleDB , the first open-source relational database...
» more
Competitive advantagesTimescaleDB is purpose-built to scale and handle time-series data workloads and is...
» more
Typical application scenariosTime-series Analytics TimescaleDB boosts the performance of PostgreSQL for time-series...
» more
Key customersTransferWise, Maersk, Walmart, Comcast, LaunchDarkly, IBM, NOV, Cisco, Nutanix, Warner...
» more
Market metricsWith over 12,700 GitHub stars and growing, 1,000,000 active databases, and an active...
» more
Licensing and pricing modelsTimescaleDB is available as a self-hosted product under two licenses, the Timescale...
» more

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More resources
Google BigQueryGridGainQuasardbTimescaleDB
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