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DBMS > Badger vs. Faircom DB vs. Percona Server for MongoDB vs. Spark SQL

System Properties Comparison Badger vs. Faircom DB vs. Percona Server for MongoDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.A drop-in replacement for MongoDB Community Edition with enterprise-grade features.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeKey-value store
Relational DBMS
Document storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score0.60
Rank#246  Overall
#39  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.faircom.com/­products/­faircom-dbwww.percona.com/­mongodb/­software/­percona-server-for-mongodbspark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.percona.com/­percona-distribution-for-mongodbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDGraph LabsFairCom CorporationPerconaApache Software Foundation
Initial release2017197920152014
Current releaseV12, November 20203.4.10-2.10, November 20173.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infoRestricted, free version availableOpen Source infoGPL Version 2Open 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 languageGoANSI C, C++C++Scala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
LinuxLinux
OS X
Windows
Data schemeschema-freeschema free, schema optional, schema required, partial schema,schema-freeyes
Typing infopredefined data types such as float or datenoyes, 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.nononono
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsnoSQL-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
proprietary protocol using JSONJDBC
ODBC
Supported programming languagesGo.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++JavaScriptno
Triggersnoyesnono
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).Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually Consistentnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, 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.noyesyes infovia In-Memory Engineno
User concepts infoAccess controlnoFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users and rolesno

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More resources
BadgerFaircom DB infoformerly c-treeACEPercona Server for MongoDBSpark SQL
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