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DBMS > Faircom DB vs. Firebolt vs. Spark SQL vs. Vitess

System Properties Comparison Faircom DB vs. Firebolt vs. Spark SQL vs. Vitess

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Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonFirebolt  Xexclude from comparisonSpark SQL  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Highly scalable cloud data warehouse and analytics product infoForked from ClickhouseSpark SQL is a component on top of 'Spark Core' for structured data processingScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelKey-value store
Relational DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
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
Score1.90
Rank#134  Overall
#62  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbwww.firebolt.iospark.apache.org/­sqlvitess.io
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.firebolt.iospark.apache.org/­docs/­latest/­sql-programming-guide.htmlvitess.io/­docs
DeveloperFairCom CorporationFirebolt Analytics Inc.Apache Software FoundationThe Linux Foundation, PlanetScale
Initial release1979202020142013
Current releaseV12, November 20203.5.0 ( 2.13), September 202315.0.2, December 2022
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++ScalaGo
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedLinux
OS X
Windows
Docker
Linux
macOS
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 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.nono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsyesSQL-like DML and DDL statementsyes infowith proprietary extensions
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
.Net
ODBC
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Go
JavaScript (Node.js)
Python
Java
Python
R
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++nonoyes infoproprietary syntax
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningyes, utilizing Spark CoreSharding
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).depending on storage layernoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentYes, 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.yesnoyes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesnoUsers with fine-grained authorization concept infono user groups or roles

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More resources
Faircom DB infoformerly c-treeACEFireboltSpark SQLVitess
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