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DBMS > Apache Drill vs. Faircom EDGE vs. Hazelcast vs. Spark SQL vs. Transbase

System Properties Comparison Apache Drill vs. Faircom EDGE vs. Hazelcast vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHazelcast  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA widely adopted in-memory data gridSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Key-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#124  Overall
#22  Document stores
#59  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitedrill.apache.orgwww.faircom.com/­products/­faircom-edgehazelcast.comspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdrill.apache.org/­docsdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlhazelcast.org/­imdg/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software FoundationFairCom CorporationHazelcastApache Software FoundationTransaction Software GmbH
Initial release20121979200820141987
Current release1.20.3, January 2023V3, October 20205.3.6, November 20233.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infoRestricted, free version availableOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++JavaScalaC and C++
Server operating systemsLinux
OS X
Windows
Android
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VMLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, 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.noyesyes infothe object must implement a serialization strategynono
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantyes infoANSI SQL queriesSQL-like query languageSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC++C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsyes info.Net, JavaScript, C/C++yes infoEvent Listeners, Executor Servicesnoyes
Triggersnoyesyes infoEventsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning infoCustomizable business rules for partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsyes infoReplicated MapnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDone or two-phase-commit; repeatable reads; read commitednoyes
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourceyesyesnono
User concepts infoAccess controlDepending on the underlying data sourceFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Role-based access controlnofine grained access rights according to SQL-standard

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More resources
Apache DrillFaircom EDGE infoformerly c-treeEDGEHazelcastSpark SQLTransbase
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