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DBMS > Amazon Neptune vs. AnzoGraph DB vs. Faircom EDGE vs. NSDb

System Properties Comparison Amazon Neptune vs. AnzoGraph DB vs. Faircom EDGE vs. NSDb

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonAnzoGraph DB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonNSDb  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelGraph DBMS
RDF store
Graph DBMS
RDF store
Key-value store
Relational DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Websiteaws.amazon.com/­neptunecambridgesemantics.com/­anzographwww.faircom.com/­products/­faircom-edgensdb.io
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlnsdb.io/­Architecture
DeveloperAmazonCambridge SemanticsFairCom Corporation
Initial release2017201819792017
Current release2.3, January 2021V3, October 2020
License infoCommercial or Open Sourcecommercialcommercial infofree trial version availablecommercial infoRestricted, free version availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++Java, Scala
Server operating systemshostedLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
macOS
Data schemeschema-freeSchema-free and OWL/RDFS-schema supportFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyes: int, bigint, decimal, string
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.nonoyesno
Secondary indexesnonoyesall fields are automatically indexed
SQL infoSupport of SQLnoSPARQL and SPARQL* as primary query language. Cypher preview.yes infoANSI SQL queriesSQL-like query language
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C++
Java
Python
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Java
Scala
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes info.Net, JavaScript, C/C++no
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic shardingFile partitioning infoCustomizable business rules for partitioningSharding
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 replication in MPP-Clusteryes infoSynchronous and asynchronous realtime replication based on transaction logs
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoKerberos/HDFS data loadingnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in MPP-ClusterImmediate Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsno infonot needed in graphsyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesUsing Apache Lucene
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users and rolesFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

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More resources
Amazon NeptuneAnzoGraph DBFaircom EDGE infoformerly c-treeEDGENSDb
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