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

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

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Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonInformix  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionJavaScript DBMS libraryNative 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 processing
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Relational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational 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
Score0.49
Rank#259  Overall
#40  Document stores
#120  Relational DBMS
Score0.24
Rank#311  Overall
#44  Key-value stores
#140  Relational DBMS
Score18.85
Rank#35  Overall
#22  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitealasql.orgwww.faircom.com/­products/­faircom-dbwww.ibm.com/­products/­informixspark.apache.org/­sql
Technical documentationgithub.com/­AlaSQL/­alasqldocs.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.html
DeveloperAndrey Gershun & Mathias R. WulffFairCom 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 Foundation
Initial release2014197919842014
Current releaseV12, November 202014.10.FC5, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoMIT-Licensecommercial infoRestricted, free version availablecommercial infofree developer edition availableOpen 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 languageJavaScriptANSI C, C++C, C++ and JavaScala
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)AIX
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
Data schemeschema-freeschema free, schema optional, schema required, partial schema,yesyes
Typing infopredefined data types such as float or datenoyes, ANSI SQL Types, JSON, typed binary structuresyes infoSince Version 12.10 support for JSON/BSON datatypesyes
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 indexesnoyesyesno
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.yes, ANSI SQL with proprietary extensionsyesSQL-like DML and DDL statements
APIs and other access methodsJavaScript APIADO.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
Supported programming languagesJavaScript.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
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++yesno
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes, 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
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integrityyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storagetunable from ACID to Eventually ConsistentACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlnoFine grained access rights according to SQL-standard with additional protections for filesUsers with fine-grained authentication, authorization, and auditing controlsno

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More resources
AlaSQLFaircom DB infoformerly c-treeACEInformixSpark SQL
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