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DBMS > Apache Kylin vs. Blazegraph vs. HBase vs. QuestDB vs. Spark SQL

System Properties Comparison Apache Kylin vs. Blazegraph vs. HBase vs. QuestDB vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonBlazegraph  Xexclude from comparisonHBase  Xexclude from comparisonQuestDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.Wide-column store based on Apache Hadoop and on concepts of BigTableA high performance open source SQL database for time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSGraph DBMS
RDF store
Wide column storeTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitekylin.apache.orgblazegraph.comhbase.apache.orgquestdb.iospark.apache.org/­sql
Technical documentationkylin.apache.org/­docswiki.blazegraph.comhbase.apache.org/­book.htmlquestdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation, originally contributed from eBay IncBlazegraphApache Software Foundation infoApache top-level project, originally developed by PowersetQuestDB Technology IncApache Software Foundation
Initial release20152006200820142014
Current release3.1.0, July 20202.1.5, March 20192.3.4, January 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoextended commercial license availableOpen Source infoApache version 2Open Source infoApache 2.0Open 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 languageJavaJavaJavaJava (Zero-GC), C++, RustScala
Server operating systemsLinuxLinux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesschema-freeschema-free, schema definition possibleyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesyes infoRDF literal typesoptions to bring your own types, AVROyesyes
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
Secondary indexesyesyesnonono
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)SPARQL is used as query languagenoSQL with time-series extensionsSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
Java API
RESTful HTTP API
Thrift
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyes infoCoprocessors in Javanono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning (by timestamps)yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Source-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in Graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)ACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infothrough memory mapped filesno
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACno
More information provided by the system vendor
Apache KylinBlazegraphHBaseQuestDBSpark SQL
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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Apache KylinBlazegraphHBaseQuestDBSpark SQL
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