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DBMS > Amazon Neptune vs. EDB Postgres vs. Firebase Realtime Database vs. Spark SQL vs. Yaacomo

System Properties Comparison Amazon Neptune vs. EDB Postgres vs. Firebase Realtime Database vs. Spark SQL vs. Yaacomo

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonEDB Postgres  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonSpark SQL  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionFast, reliable graph database built for the cloudThe EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.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 processingOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelGraph DBMS
RDF store
Relational DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score1.90
Rank#135  Overall
#63  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunewww.enterprisedb.comfirebase.google.com/­products/­realtime-databasespark.apache.org/­sqlyaacomo.com
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.enterprisedb.com/­docsfirebase.google.com/­docs/­databasespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonEnterpriseDBGoogle infoacquired by Google 2014Apache Software FoundationQ2WEB GmbH
Initial release20172005201220142009
Current release14, December 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infoBSD for PostgreSQL-componentscommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCScala
Server operating systemshostedLinux
Windows
hostedLinux
OS X
Windows
Android
Linux
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 infospecific XML-type available, but no XML query functionality.nonono
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLnoyes infostandard with numerous extensionsnoSQL-like DML and DDL statementsyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Android
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
Java
JavaScript
Objective-C
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.limited functionality with using 'rules'no
TriggersnoyesCallbacks are triggered when data changesnoyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning infoby hash, list or rangeyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.Multi-source replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardyes, based on authentication and database rulesnofine grained access rights according to SQL-standard

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More resources
Amazon NeptuneEDB PostgresFirebase Realtime DatabaseSpark SQLYaacomo
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