DBMS > Amazon Neptune vs. Apache Kylin vs. RDF4J
System Properties Comparison Amazon Neptune vs. Apache Kylin vs. RDF4J
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|Editorial information provided by DB-Engines|
|Name||Amazon Neptune Xexclude from comparison||Apache Kylin Xexclude from comparison||RDF4J formerly known as Sesame Xexclude from comparison|
|Description||Fast, reliable graph database built for the cloud||A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack||RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.|
|Primary database model||Graph DBMS|
|Relational DBMS||RDF store|
|Developer||Amazon||Apache Software Foundation, originally contributed from eBay Inc||Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.|
|Current release||3.1.0, July 2020|
|License Commercial or Open Source||commercial||Open Source Apache Version 2.0||Open Source Eclipse Distribution License (EDL), v1.0.|
|Cloud-based only Only available as a cloud service||yes||no||no|
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|Server operating systems||hosted||Linux||Linux|
|Data scheme||schema-free||yes||yes RDF Schemas|
|Typing predefined data types such as float or date||yes||yes||yes|
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.||no||no|
|SQL Support of SQL||no||ANSI SQL for queries (using Apache Calcite)||no|
|APIs and other access methods||OpenCypher|
RDF 1.1 / SPARQL 1.1
RESTful HTTP API
RIO RDF Input/Output
SeRQL Sesame RDF Query Language
Sesame REST HTTP Protocol
|Supported programming languages||C#|
|Server-side scripts Stored procedures||no||yes|
|Partitioning methods Methods for storing different data on different nodes||none||none|
|Replication methods Methods for redundantly storing data on multiple nodes||Multi-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.||none|
|MapReduce Offers an API for user-defined Map/Reduce methods||no||yes||no|
|Consistency concepts Methods to ensure consistency in a distributed system||Immediate Consistency||Immediate Consistency|
|Foreign keys Referential integrity||yes Relationships in graphs|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID||ACID Isolation support depends on the API used|
|Concurrency Support for concurrent manipulation of data||yes||yes||yes|
|Durability Support for making data persistent||yes with encyption-at-rest||yes||yes in-memory storage is supported as well|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||no|
|User concepts Access control||Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)||no|
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|Amazon Neptune||Apache Kylin||RDF4J formerly known as Sesame|
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