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DBMS > Kyligence Enterprise vs. ReductStore vs. Spark SQL

System Properties Comparison Kyligence Enterprise vs. ReductStore vs. Spark SQL

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Editorial information provided by DB-Engines
NameKyligence Enterprise  Xexclude from comparisonReductStore  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed analytics engine for big data, built on top of Apache KylinDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#266  Overall
#124  Relational DBMS
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitekyligence.io/­kyligence-enterprisegithub.com/­reductstore
www.reduct.store
spark.apache.org/­sql
Technical documentationwww.reduct.store/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKyligence, Inc.ReductStore LLCApache Software Foundation
Initial release201620232014
Current release1.9, March 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoBusiness Source License 1.1Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, RustScala
Server operating systemsLinuxDocker
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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.nono
Secondary indexesyesno
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)SQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP APIJDBC
ODBC
Supported programming languagesC++
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
Server-side scripts infoStored proceduresno
Triggersno
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlno

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More resources
Kyligence EnterpriseReductStoreSpark SQL
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