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DBMS > Faircom DB vs. Hazelcast vs. JaguarDB vs. Spark SQL

System Properties Comparison Faircom DB vs. Hazelcast vs. JaguarDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonHazelcast  Xexclude from comparisonJaguarDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.A widely adopted in-memory data gridPerformant, highly scalable DBMS for AI and IoT applicationsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value store
Relational DBMS
Key-value storeKey-value store
Vector DBMS
Relational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbhazelcast.comwww.jaguardb.comspark.apache.org/­sql
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlhazelcast.org/­imdg/­docswww.jaguardb.com/­support.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFairCom CorporationHazelcastDataJaguar, Inc.Apache Software Foundation
Initial release1979200820152014
Current releaseV12, November 20205.3.6, November 20233.3 July 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL V3.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++JavaC++ infothe server part. Clients available in other languagesScala
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
All OS with a Java VMLinuxLinux
OS X
Windows
Data schemeschema free, schema optional, schema required, partial schema,schema-freeyesyes
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyesyesyes
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.noyes infothe object must implement a serialization strategynono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsSQL-like query languageA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like DML and DDL statements
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
JDBC
ODBC
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yes infoEvent Listeners, Executor Servicesnono
Triggersyesyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yes infoReplicated MapMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually Consistentone or two-phase-commit; repeatable reads; read commitednono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesRole-based access controlrights management via user accountsno

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More resources
Faircom DB infoformerly c-treeACEHazelcastJaguarDBSpark SQL
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