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DBMS > Amazon DocumentDB vs. Blazegraph vs. Fujitsu Enterprise Postgres vs. Hive vs. Spark SQL

System Properties Comparison Amazon DocumentDB vs. Blazegraph vs. Fujitsu Enterprise Postgres vs. Hive vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonBlazegraph  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonHive  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.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.data warehouse software for querying and managing large distributed datasets, built on HadoopSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeGraph DBMS
RDF store
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score0.75
Rank#219  Overall
#19  Graph DBMS
#8  RDF stores
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­documentdbblazegraph.comwww.postgresql.fastware.comhive.apache.orgspark.apache.org/­sql
Technical documentationaws.amazon.com/­documentdb/­resourceswiki.blazegraph.comwww.postgresql.fastware.com/­product-manualscwiki.apache.org/­confluence/­display/­Hive/­Homespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBlazegraphPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyApache Software Foundation infoinitially developed by FacebookApache Software Foundation
Initial release2019200620122014
Current release2.1.5, March 2019Fujitsu Enterprise Postgres 14, January 20223.1.3, April 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoextended commercial license availablecommercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJavaScala
Server operating systemshostedLinux
OS X
Windows
Linux
Windows
All OS with a Java VMLinux
OS X
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes infoRDF literal typesyesyesyes
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 indexesyesyesyesyesno
SQL infoSupport of SQLnoSPARQL is used as query languageyesSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Thrift
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesuser defined functionsyes infouser defined functions and integration of map-reduceno
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingpartitioning by range, list and by hashShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesSource-replica replicationselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonoyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infoRelationships in Graphsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
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.no
User concepts infoAccess controlAccess rights for users and rolesSecurity and Authentication via Web Application Container (Tomcat, Jetty)fine grained access rights according to SQL-standardAccess rights for users, groups and rolesno
More information provided by the system vendor
Amazon DocumentDBBlazegraphFujitsu Enterprise PostgresHiveSpark SQL
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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More resources
Amazon DocumentDBBlazegraphFujitsu Enterprise PostgresHiveSpark SQL
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