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DBMS > Apache Kylin vs. Databricks vs. Faircom DB vs. Hawkular Metrics vs. TerarkDB

System Properties Comparison Apache Kylin vs. Databricks vs. Faircom DB vs. Hawkular Metrics vs. TerarkDB

Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonDatabricks  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelRelational DBMSDocument store
Relational DBMS
Key-value store
Relational DBMS
Time Series DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitekylin.apache.orgwww.databricks.comwww.faircom.com/­products/­faircom-dbwww.hawkular.orggithub.com/­bytedance/­terarkdb
Technical documentationkylin.apache.org/­docsdocs.databricks.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidebytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software Foundation, originally contributed from eBay IncDatabricksFairCom CorporationCommunity supported by Red HatByteDance, originally Terark
Initial release20152013197920142016
Current release3.1.0, July 2020V12, November 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infoRestricted, free version availableOpen Source infoApache 2.0commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++JavaC++
Server operating systemsLinuxhostedAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema free, schema optional, schema required, partial schema,schema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesno
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.noyesnonono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)with Databricks SQLyes, ANSI SQL with proprietary extensionsnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
HTTP RESTC++ API
Java API
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Go
Java
Python
Ruby
C++
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes info.Net, JavaScript, C/C++nono
Triggersyesyes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding infobased on Cassandranone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).selectable replication factor infobased on Cassandranone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually Consistentnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesnoyes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesnono
More information provided by the system vendor
Apache KylinDatabricksFaircom DB infoformerly c-treeACEHawkular MetricsTerarkDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache KylinDatabricksFaircom DB infoformerly c-treeACEHawkular MetricsTerarkDB
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