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DBMS > Badger vs. FatDB vs. Hazelcast vs. RavenDB vs. Spark SQL

System Properties Comparison Badger vs. FatDB vs. Hazelcast vs. RavenDB vs. Spark SQL

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonFatDB  Xexclude from comparisonHazelcast  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A .NET NoSQL DBMS that can integrate with and extend SQL Server.A widely adopted in-memory data gridOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeDocument store
Key-value store
Key-value storeDocument storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score2.92
Rank#101  Overall
#18  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerhazelcast.comravendb.netspark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerhazelcast.org/­imdg/­docsravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDGraph LabsFatCloudHazelcastHibernating RhinosApache Software Foundation
Initial release20172012200820102014
Current release5.3.6, November 20235.4, July 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC#JavaC#Scala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
WindowsAll OS with a Java VMLinux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyesyesnoyes
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.noyes infothe object must implement a serialization strategyno
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSQL-like query languageSQL-like query language (RQL)SQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
ODBC
Supported programming languagesGoC#.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsyes infoEvent Listeners, Executor Servicesyesno
Triggersnoyes infovia applicationsyes infoEventsyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factoryes infoReplicated MapMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoone or two-phase-commit; repeatable reads; read commitedACID, Cluster-wide transaction availableno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnono infoCan implement custom security layer via applicationsRole-based access controlAuthorization levels configured per client per databaseno

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More resources
BadgerFatDBHazelcastRavenDBSpark SQL
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