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DBMS > Apache Kylin vs. Apache Pinot vs. Atos Standard Common Repository vs. GridDB vs. Hawkular Metrics

System Properties Comparison Apache Kylin vs. Apache Pinot vs. Atos Standard Common Repository vs. GridDB vs. Hawkular Metrics

Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonApache Pinot  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonGridDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksScalable in-memory time series database optimized for IoT and Big DataHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.
Primary database modelRelational DBMSRelational DBMSDocument store
Key-value store
Time Series DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Websitekylin.apache.orgpinot.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorygriddb.netwww.hawkular.org
Technical documentationkylin.apache.org/­docsdocs.pinot.apache.orgdocs.griddb.netwww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperApache Software Foundation, originally contributed from eBay IncApache Software Foundation and contributorsAtos Convergence CreatorsToshiba CorporationCommunity supported by Red Hat
Initial release20152015201620132014
Current release3.1.0, July 20201.0.0, September 202317035.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJavaC++Java
Server operating systemsLinuxAll OS with a Java JDK11 or higherLinuxLinuxLinux
OS X
Windows
Data schemeyesyesSchema and schema-less with LDAP viewsyesschema-free
Typing infopredefined data types such as float or dateyesyesoptionalyes infonumerical, string, blob, geometry, boolean, timestampyes
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.noyesnono
Secondary indexesyesyesyesno
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)SQL-like query languagenoSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCLDAPJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP REST
Supported programming languagesGo
Java
Python
All languages with LDAP bindingsC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresnonono
Triggersyesyesyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infocell divisionShardingSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate consistency within container, eventual consistency across containersEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlLDAP bind authenticationAccess rights for users can be defined per databaseno
More information provided by the system vendor
Apache KylinApache PinotAtos Standard Common RepositoryGridDBHawkular Metrics
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
Apache KylinApache PinotAtos Standard Common RepositoryGridDBHawkular Metrics
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