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DBMS > Amazon Neptune vs. Apache Impala vs. Datomic vs. Stardog

System Properties Comparison Amazon Neptune vs. Apache Impala vs. Datomic vs. Stardog

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSGraph DBMS
RDF store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Websiteaws.amazon.com/­neptuneimpala.apache.orgwww.datomic.comwww.stardog.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesimpala.apache.org/­impala-docs.htmldocs.datomic.comdocs.stardog.com
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectStardog-Union
Initial release2017201320122010
Current release4.1.0, June 20221.0.7075, December 20237.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercial infolimited edition freecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, ClojureJava
Server operating systemshostedLinuxAll OS with a Java VMLinux
macOS
Windows
Data schemeschema-freeyesyesschema-free and OWL/RDFS-schema support
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.nononono infoImport/export of XML data possible
Secondary indexesnoyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP APIGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBCClojure
Java
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyes infoTransaction Functionsuser defined functions and aggregates, HTTP Server extensions in Java
TriggersnonoBy using transaction functionsyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnone infoBut extensive use of caching in the application peersnone
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.selectable replication factornone infoBut extensive use of caching in the application peersMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyes inforelationships in graphs
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-restyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess rights for users and roles

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More resources
Amazon NeptuneApache ImpalaDatomicStardog
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