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DBMS > Apache Kylin vs. Google BigQuery vs. GridGain vs. Quasardb

System Properties Comparison Apache Kylin vs. Google BigQuery vs. GridGain vs. Quasardb

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonGridGain  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackLarge scale data warehouse service with append-only tablesGridGain is an in-memory computing platform, built on Apache IgniteDistributed, high-performance timeseries database
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitekylin.apache.orgcloud.google.com/­bigquerywww.gridgain.comquasar.ai
Technical documentationkylin.apache.org/­docscloud.google.com/­bigquery/­docswww.gridgain.com/­docs/­index.htmldoc.quasar.ai/­master
DeveloperApache Software Foundation, originally contributed from eBay IncGoogleGridGain Systems, Inc.quasardb
Initial release2015201020072009
Current release3.1.0, July 2020GridGain 8.5.13.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetC++
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
BSD
Linux
OS X
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infointeger and binary
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.nonoyesno
Secondary indexesyesnoyesyes infowith tags
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)yesANSI-99 for query and DML statements, subset of DDLSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP/JSON APIHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP API
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
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptyes (compute grid and cache interceptors can be used instead)no
Triggersnoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Source-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes (compute grid and hadoop accelerator)with Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes infoTransient mode
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 trail

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More resources
Apache KylinGoogle BigQueryGridGainQuasardb
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