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DBMS > Faircom DB vs. Informix vs. Spark SQL vs. SQL.JS

System Properties Comparison Faircom DB vs. Informix vs. Spark SQL vs. SQL.JS

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Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonInformix  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQL.JS  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataSpark SQL is a component on top of 'Spark Core' for structured data processingPort of SQLite to JavaScript
Primary database modelKey-value store
Relational DBMS
Relational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
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
Score17.87
Rank#35  Overall
#22  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.53
Rank#252  Overall
#116  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbwww.ibm.com/­products/­informixspark.apache.org/­sqlsql.js.org
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
spark.apache.org/­docs/­latest/­sql-programming-guide.htmlsql.js.org/­documentation/­index.html
DeveloperFairCom CorporationIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Apache Software FoundationAlon Zakai infoenhancements implemented by others
Initial release1979198420142012
Current releaseV12, November 202014.10.FC5, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercial infofree developer edition availableOpen Source infoApache 2.0Open Source
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++C, C++ and JavaScalaJavaScript
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
AIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeschema free, schema optional, schema required, partial schema,yesyesyes
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyes infoSince Version 12.10 support for JSON/BSON datatypesyesyes
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.nonono
Secondary indexesyesyesno
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsyesSQL-like DML and DDL statementsyes infoSQL-92 is not fully supported
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
JavaScript API
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yesnono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingyes, utilizing Spark Corenone
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).Multi-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistencynone
Foreign keys infoReferential integrityyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyesno infoexcept by serializing a db to a file
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesUsers with fine-grained authentication, authorization, and auditing controlsnono

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More resources
Faircom DB infoformerly c-treeACEInformixSpark SQLSQL.JS
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