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DBMS > atoti vs. Badger vs. Blazegraph vs. Spark SQL

System Properties Comparison atoti vs. Badger vs. Blazegraph vs. Spark SQL

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonBadger  Xexclude from comparisonBlazegraph  Xexclude from comparisonSpark SQL  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelObject oriented DBMSKey-value storeGraph DBMS
RDF store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatoti.iogithub.com/­dgraph-io/­badgerblazegraph.comspark.apache.org/­sql
Technical documentationdocs.atoti.iogodoc.org/­github.com/­dgraph-io/­badgerwiki.blazegraph.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperActiveViamDGraph LabsBlazegraphApache Software Foundation
Initial release201720062014
Current release2.1.5, March 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache 2.0Open Source infoextended commercial license 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 languageJavaGoJavaScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyes infoRDF literal typesyes
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 indexesnoyesno
SQL infoSupport of SQLMultidimensional Expressions (MDX)noSPARQL is used as query languageSQL-like DML and DDL statements
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
JDBC
ODBC
Supported programming languagesGo.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresPythonnoyesno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infoRelationships in Graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlnoSecurity and Authentication via Web Application Container (Tomcat, Jetty)no

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atotiBadgerBlazegraphSpark SQL
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