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DBMS > Axibase vs. Faircom EDGE vs. Hawkular Metrics vs. RDF4J vs. Spark SQL

System Properties Comparison Axibase vs. Faircom EDGE vs. Hawkular Metrics vs. RDF4J vs. Spark SQL

Editorial information provided by DB-Engines
NameAxibase  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Time Series DBMSRDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#292  Overall
#25  Time Series DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaxibase.com/­docs/­atsd/­financewww.faircom.com/­products/­faircom-edgewww.hawkular.orgrdf4j.orgspark.apache.org/­sql
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guiderdf4j.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAxibase CorporationFairCom CorporationCommunity supported by Red HatSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Apache Software Foundation
Initial release20131979201420042014
Current release15585V3, October 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidcommercial infoRestricted, free version availableOpen Source infoApache 2.0Open Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++JavaJavaScala
Server operating systemsLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Windows
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyes infoshort, integer, long, float, double, decimal, stringyes, ANSI Standard SQL Typesyesyesyes
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.noyesnono
Secondary indexesnoyesnoyesno
SQL infoSupport of SQLSQL-like query languageyes infoANSI SQL queriesnonoSQL-like DML and DDL statements
APIs and other access methodsJDBC
Proprietary protocol (Network API)
RESTful HTTP API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
HTTP RESTJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
Supported programming languagesGo
Java
PHP
Python
R
Ruby
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Go
Java
Python
Ruby
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyes info.Net, JavaScript, C/C++noyesno
Triggersyesyesyes infovia Hawkular Alertingyesno
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning infoCustomizable business rules for partitioningSharding infobased on Cassandranoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoSynchronous and asynchronous realtime replication based on transaction logsselectable replication factor infobased on Cassandranonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynoyes infowhen using SQLnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.nonono

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More resources
AxibaseFaircom EDGE infoformerly c-treeEDGEHawkular MetricsRDF4J infoformerly known as SesameSpark SQL
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