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DBMS > Amazon Neptune vs. Apache Druid vs. EDB Postgres vs. Spark SQL vs. Yaacomo

System Properties Comparison Amazon Neptune vs. Apache Druid vs. EDB Postgres vs. Spark SQL vs. Yaacomo

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Druid  Xexclude from comparisonEDB Postgres  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 cloudOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataThe 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.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 DBMS
Time Series DBMS
Relational DBMSRelational 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
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.90
Rank#135  Overall
#63  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunedruid.apache.orgwww.enterprisedb.comspark.apache.org/­sqlyaacomo.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdruid.apache.org/­docs/­latest/­designwww.enterprisedb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonApache Software Foundation and contributorsEnterpriseDBApache Software FoundationQ2WEB GmbH
Initial release20172012200520142009
Current release29.0.1, April 202414, December 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2commercial infoBSD for PostgreSQL-componentsOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCScala
Server operating systemshostedLinux
OS X
Unix
Linux
Windows
Linux
OS X
Windows
Android
Linux
Windows
Data schemeschema-freeyes infoschema-less columns are supportedyesyesyes
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.nonoyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLnoSQL for queryingyes infostandard with numerous extensionsSQL-like DML and DDL statementsyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infomanual/auto, time-basedhorizontal 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.yes, via HDFS, S3 or other storage enginesMulti-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 ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
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.nononoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)RBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
Amazon NeptuneApache DruidEDB PostgresSpark SQLYaacomo
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