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DBMS > Apache Impala vs. Apache Kylin vs. GridDB vs. Stardog

System Properties Comparison Apache Impala vs. Apache Kylin vs. GridDB vs. Stardog

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Kylin  Xexclude from comparisonGridDB  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackScalable in-memory time series database optimized for IoT and Big DataEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSRelational DBMSTime Series DBMSGraph DBMS
RDF store
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Websiteimpala.apache.orgkylin.apache.orggriddb.netwww.stardog.com
Technical documentationimpala.apache.org/­impala-docs.htmlkylin.apache.org/­docsdocs.griddb.netdocs.stardog.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation, originally contributed from eBay IncToshiba CorporationStardog-Union
Initial release2013201520132010
Current release4.1.0, June 20223.1.0, July 20205.1, August 20227.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++Java
Server operating systemsLinuxLinuxLinuxLinux
macOS
Windows
Data schemeyesyesyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesyes 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.nononono infoImport/export of XML data possible
Secondary indexesyesyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI SQL for queries (using Apache Calcite)SQL92, SQL-like TQL (Toshiba Query Language)Yes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynonoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACID
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.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databaseAccess rights for users and roles
More information provided by the system vendor
Apache ImpalaApache KylinGridDBStardog
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache ImpalaApache KylinGridDBStardog
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