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DBMS > Amazon Neptune vs. GRAKN.AI vs. TimescaleDB

System Properties Comparison Amazon Neptune vs. GRAKN.AI vs. TimescaleDB

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGRAKN.AI  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudGrakn is a distributed, hyper-relational database for managing complex data that serves as a knowledge base for cognitive/AI systems.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelGraph DBMS
RDF store
Graph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.57
Rank#125  Overall
#7  Graph DBMS
#4  RDF stores
Score0.23
Rank#248  Overall
#19  Graph DBMS
#116  Relational DBMS
Score1.79
Rank#117  Overall
#8  Time Series DBMS
Websiteaws.amazon.com/­neptunegrakn.aiwww.timescale.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdev.grakn.ai/­docsdocs.timescale.com
DeveloperAmazonGrakn Labs LtdTimescale
Initial release201720162017
Current release1.6.1, December 2019
License infoCommercial or Open SourcecommercialOpen Source infoGPL Version 3, commercial licenses availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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
Secondary indexesnoyesyes
SQL infoSupport of SQLnonoyes infofull PostgreSQL SQL syntax
APIs and other access methodsRDF 1.1 / SPARQL 1.1
TinkerPop Gremlin 3.3
console (shell)
gRPC protocol
Workbase (visualisation software)
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoby using Cassandrayes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicasMaster-master replication infoby using CassandraMaster-slave replication with hot standby and reads on slaves info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoby using Apache Kafka and Apache Zookeeperno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsno infosubstituted by the relationship featureyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes
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)yes infoat REST API level; other APIs in progressfine grained access rights according to SQL-standard
More information provided by the system vendor
Amazon NeptuneGRAKN.AITimescaleDB
Specific characteristicsGrakn is the knowledge graph to organise complex networks of data and making it queryable,...
» more
TimescaleDB is the first open-source time-series database that combines the reliability,...
» more
Competitive advantagesExpressive and flexible data model: The meta-schema of Grakn allows for modelling...
» more
TimescaleDB is purpose-built to scale and handle time-series data workloads and is...
» more
Typical application scenariosLife sciences : Grakn makes working with biological data much easier and accelerates...
» more
IoT, Industrial Machine, and Sensor Data Various industrial IoT use cases across...
» more
Key customersAltair Engineering Inc., Bloomberg, Comcast, Cray, Cree, DNSFilter, Laika, LaunchDarkly,...
» more
Market metrics1.8 million+ downloads, 7,500+ Github stars
» more
Licensing and pricing modelsAGPL and Commercial . The commercial license is priced based on cluster resources...
» more
Apache 2 and Timescale License (TSL); Product matrix here ; information on pricing...
» more

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More resources
Amazon NeptuneGRAKN.AITimescaleDB
Conferences and events

Grakn Cosmos, the universal conference of technologies built using Grakn
London, UK, 6-7 February 2020

Recent citations in the news

Catching up with Amazon Neptune
26 November 2019, ZDNet

Amazon Neptune review: A scalable graph database for OLTP
13 May 2019, InfoWorld

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Amazon cloud database and data analytics expand
4 December 2019, TechTarget

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GRAKN.AI: How Haikal Pribadi went from being a refugee to building a database for AI systems
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TimescaleDB Delivers Another Option for Time-Series Analytics
17 October 2019, Datanami

Timescale announces $15M investment and new enterprise version of TimescaleDB
29 January 2019, TechCrunch

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

Why time series databases are exploding in popularity
26 June 2019, TechRepublic

The First Complete Life-Cycle Database Management Solution for TimescaleDB
16 April 2019, PRNewswire

provided by Google News

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