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DBMS > Blueflood vs. Faircom DB vs. Firebase Realtime Database vs. Spark SQL vs. SWC-DB

System Properties Comparison Blueflood vs. Faircom DB vs. Firebase Realtime Database vs. Spark SQL vs. SWC-DB

Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Spark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMS
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Document storeRelational DBMSWide column store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#346  Overall
#33  Time Series DBMS
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.08
Rank#364  Overall
#13  Wide column stores
Websiteblueflood.iowww.faircom.com/­products/­faircom-dbfirebase.google.com/­products/­realtime-databasespark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlfirebase.google.com/­docs/­databasespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperRackspaceFairCom CorporationGoogle infoacquired by Google 2014Apache Software FoundationAlex Kashirin
Initial release20131979201220142020
Current releaseV12, November 20203.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infoRestricted, free version availablecommercialOpen Source infoApache 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++ScalaC++
Server operating systemsLinux
OS X
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedLinux
OS X
Windows
Linux
Data schemepredefined schemeschema free, schema optional, schema required, partial schema,schema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyes
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.nonononono
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsnoSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsHTTP RESTADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Android
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
Thrift
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Java
JavaScript
Objective-C
Java
Python
R
Scala
C++
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++limited functionality with using 'rules'nono
TriggersnoyesCallbacks are triggered when data changesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandrayes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually Consistentyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesYes, 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.noyesnono
User concepts infoAccess controlnoFine grained access rights according to SQL-standard with additional protections for filesyes, based on authentication and database rulesno

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More resources
BluefloodFaircom DB infoformerly c-treeACEFirebase Realtime DatabaseSpark SQLSWC-DB infoSuper Wide Column Database
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