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DBMS > Apache Kylin vs. Brytlyt vs. Google Cloud Datastore vs. Stardog

System Properties Comparison Apache Kylin vs. Brytlyt vs. Google Cloud Datastore vs. Stardog

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonBrytlyt  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSRelational DBMSDocument storeGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.14
Rank#171  Overall
#77  Relational DBMS
Score0.27
Rank#292  Overall
#132  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score1.93
Rank#121  Overall
#10  Graph DBMS
#6  RDF stores
Websitekylin.apache.orgbrytlyt.iocloud.google.com/­datastorewww.stardog.com
Technical documentationkylin.apache.org/­docsdocs.brytlyt.iocloud.google.com/­datastore/­docsdocs.stardog.com
DeveloperApache Software Foundation, originally contributed from eBay IncBrytlytGoogleStardog-Union
Initial release2015201620082010
Current release3.1.0, July 20205.0, August 20237.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial 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 servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++ and CUDAJava
Server operating systemsLinuxLinux
OS X
Windows
hostedLinux
macOS
Windows
Data schemeyesyesschema-freeschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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.noyes infospecific XML-type available, but no XML query functionality.nono infoImport/export of XML data possible
Secondary indexesyesyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)yesSQL-like query language (GQL)Yes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
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 languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLusing Google App Engineuser defined functions and aggregates, HTTP Server extensions in Java
TriggersyesCallbacks using the Google Apps Engineyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using PaxosMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
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.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles

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More resources
Apache KylinBrytlytGoogle Cloud DatastoreStardog
Recent citations in the news

Overhauling Apache Kylin for the cloud
18 November 2021, InfoWorld

Migrating from ClickHouse to Apache Doris: Boosting OLAP Performance
9 October 2023, hackernoon.com

eBay’s Kylin Becomes a Top-Level Apache Open Source Project
9 December 2015, eBay Inc.

Distributed OLAPer Kyligence accelerates core engine, adds real-time data support
10 August 2021, Blocks & Files

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9 November 2022, AWS Blog

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1 August 2023, PR Newswire

Bringing GPUs To Bear On Bog Standard Relational Databases
26 February 2018, The Next Platform

London’s Brytlyt raises €4.4 million for its data analytics and visualisation technology
22 December 2021, EU-Startups

Brytlyt Unleashes Serverless GPU-Acceleration for Analytics
15 September 2021, PR Newswire

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