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DBMS > Apache Kylin vs. Microsoft Azure Cosmos DB vs. PieCloudDB vs. Solr

System Properties Comparison Apache Kylin vs. Microsoft Azure Cosmos DB vs. PieCloudDB vs. Solr

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonPieCloudDB  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackGlobally distributed, horizontally scalable, multi-model database serviceA cloud-native analytic database platform with new technologoy for elastic MPPA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMSSearch engine
Secondary database modelsSpatial DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score29.04
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score0.25
Rank#304  Overall
#138  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitekylin.apache.orgazure.microsoft.com/­services/­cosmos-dbwww.openpie.comsolr.apache.org
Technical documentationkylin.apache.org/­docslearn.microsoft.com/­azure/­cosmos-dbsolr.apache.org/­resources.html
DeveloperApache Software Foundation, originally contributed from eBay IncMicrosoftOpenPieApache Software Foundation
Initial release201520142006
Current release3.1.0, July 20202.1, January 20239.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsLinuxhostedhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyes infoJSON typesyesyes infosupports customizable data types and automatic typing
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
Secondary indexesyesyes infoAll properties auto-indexed by defaultyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)SQL-like query languageyesSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
CLI Client
JDBC
ODBC
Java API
RESTful HTTP/JSON API
Supported programming languages.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
Java
PL/SQL
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresJavaScriptuser defined functionsJava plugins
TriggersJavaScriptnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceyesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyeswith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*spark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataMulti-item ACID transactions with snapshot isolation within a partitionACIDoptimistic locking
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.noyes
User concepts infoAccess controlAccess rights can be defined down to the item levelUser Roles and pluggable authentication with full SQL Standardyes
More information provided by the system vendor
Apache KylinMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBPieCloudDBSolr
Specific characteristicsPieCloudDB, OpenPie's flagship product, is a cutting-edge cloud-native data warehouse....
» more
Competitive advantagesExtreme Elastic: PieCloudDB utilizes a cutting-edge eMPP cloud-native architecture...
» more
Typical application scenariosPieCloudDB is ideal for Data mining applications that require extreme scalability...
» more
Key customersSail-Cloud China Shipbuilding Group Haizhou System Soochow Securities ​etc.,
» more
Licensing and pricing modelsPieCloudDB Community Edition: Community License, Free Download, Self-Hosted Deployment;...
» more

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More resources
Apache KylinMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBPieCloudDBSolr
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