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DBMS > Amazon Neptune vs. Apache Druid vs. Citus vs. Netezza

System Properties Comparison Amazon Neptune vs. Apache Druid vs. Citus vs. Netezza

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Druid  Xexclude from comparisonCitus  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLData warehouse and analytics appliance part of IBM PureSystems
Primary database modelGraph DBMS
RDF store
Relational DBMS
Time Series DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
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
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websiteaws.amazon.com/­neptunedruid.apache.orgwww.citusdata.comwww.ibm.com/­products/­netezza
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdruid.apache.org/­docs/­latest/­designdocs.citusdata.com
DeveloperAmazonApache Software Foundation and contributorsIBM
Initial release2017201220102000
Current release29.0.1, April 20248.1, December 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2Open Source infoAGPL, commercial license also availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC
Server operating systemshostedLinux
OS X
Unix
LinuxLinux infoincluded in appliance
Data schemeschema-freeyes infoschema-less columns are supportedyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoSQL for queryingyes infostandard, with numerous extensionsyes
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
OLE DB
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnonouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infomanual/auto, time-basedShardingSharding
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 enginesSource-replica replication infoother methods possible by using 3rd party extensionsSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
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-standardUsers with fine-grained authorization concept

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More resources
Amazon NeptuneApache DruidCitusNetezza infoAlso called PureData System for Analytics by IBM
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