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DBMS > FileMaker vs. Heroic vs. Hive vs. Ignite vs. Spark SQL

System Properties Comparison FileMaker vs. Heroic vs. Hive vs. Ignite vs. Spark SQL

Editorial information provided by DB-Engines
NameFileMaker  Xexclude from comparisonHeroic  Xexclude from comparisonHive  Xexclude from comparisonIgnite  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFileMaker is a cross-platform RDBMS that includes a GUI frontend.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchdata warehouse software for querying and managing large distributed datasets, built on HadoopApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSRelational DBMSKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score47.91
Rank#20  Overall
#14  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.claris.com/­filemakergithub.com/­spotify/­heroichive.apache.orgignite.apache.orgspark.apache.org/­sql
Technical documentationwww.claris.com/­resources/­documentationspotify.github.io/­heroiccwiki.apache.org/­confluence/­display/­Hive/­Homeapacheignite.readme.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperClaris infoa subsidiary of AppleSpotifyApache Software Foundation infoinitially developed by FacebookApache Software FoundationApache Software Foundation
Initial release19832014201220152014
Current release19.4.1, November 20213.1.3, April 2022Apache Ignite 2.63.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open 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 languageJavaJavaC++, Java, .NetScala
Server operating systemsiOS infoclient part only
Linux
OS X
Windows
All OS with a Java VMLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.yes infoA http query request can return the data in XML formatnoyesno
Secondary indexesyesyes infovia Elasticsearchyesyesno
SQL infoSupport of SQLyes infovia pluginsnoSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statements
APIs and other access methodsFilemaker WebDirect
JDBC
ODBC
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Supported programming languagesPHPC++
Java
PHP
Python
C#
C++
Java
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnoyes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)no
Triggersyesnonoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication, warm standby infosince Version 14yesselectable replication factoryes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDno
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.noyesno
User concepts infoAccess controlsimple rights management via user accounts and connection to external directory servicesAccess rights for users, groups and rolesSecurity Hooks for custom implementationsno

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More resources
FileMakerHeroicHiveIgniteSpark SQL
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