DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon Neptune vs. FoundationDB vs. JanusGraph vs. Lovefield

System Properties Comparison Amazon Neptune vs. FoundationDB vs. JanusGraph vs. Lovefield

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonFoundationDB  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonLovefield  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionFast, reliable graph database built for the cloudOrdered key-value store. Core features are complimented by layers.A Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Embeddable relational database for web apps written in pure JavaScript
Primary database modelGraph DBMS
RDF store
Document store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Graph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Websiteaws.amazon.com/­neptunegithub.com/­apple/­foundationdbjanusgraph.orggoogle.github.io/­lovefield
Technical documentationaws.amazon.com/­neptune/­developer-resourcesapple.github.io/­foundationdbdocs.janusgraph.orggithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.md
DeveloperAmazonFoundationDBLinux Foundation; originally developed as Titan by AureliusGoogle
Initial release2017201320172014
Current release6.2.28, November 20200.6.3, February 20232.1.12, February 2017
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJavaScript
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Unix
Windows
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, Safari
Data schemeschema-freeschema-free infosome layers support schemasyesyes
Typing infopredefined data types such as float or dateyesno infosome layers support typingyesyes
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.nonono
Secondary indexesnonoyesyes
SQL infoSupport of SQLnosupported in specific SQL layer onlynoSQL-like query language infovia JavaScript builder pattern
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
Clojure
Java
Python
JavaScript
Server-side scripts infoStored proceduresnoin SQL-layer onlyyesno
TriggersnonoyesUsing read-only observers
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)none
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.yesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infovia Faunus, a graph analytics engineno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyLinearizable consistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsin SQL-layer onlyyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes, by using IndexedDB or the cloud service Firebase Realtime Database
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infousing MemoryDB
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noUser authentification and security via Rexster Graph Serverno

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Amazon NeptuneFoundationDBJanusGraph infosuccessor of TitanLovefield
Recent citations in the news

AWS announces Amazon Neptune I/O-Optimized
22 February 2024, AWS Blog

Amazon Neptune Analytics is now available in the AWS Europe (London) Region
14 March 2024, AWS Blog

Find and link similar entities in a knowledge graph using Amazon Neptune, Part 1: Full-text search | Amazon Web ...
7 May 2024, AWS Blog

Amazon Neptune Analytics is now generally available
29 November 2023, AWS Blog

Find and link similar entities in a knowledge graph using Amazon Neptune, Part 2: Vector similarity search | Amazon ...
7 May 2024, AWS Blog

provided by Google News

FoundationDB team's new venture, Antithesis, raises $47M to enhance software testing
13 February 2024, SiliconANGLE News

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
12 March 2024, Datanami

Antithesis raises $47M to launch an automated testing platform for software
13 February 2024, TechCrunch

Antithesis Launches Out Of Stealth To Revolutionize Software Reliability
13 February 2024, Yahoo Finance

Deno adds scaleable messaging with new Queues feature, sparks debate about proprietary services • DEVCLASS
28 September 2023, DevClass

provided by Google News

Database Deep Dives: JanusGraph
8 August 2019, ibm.com

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

From graph db to graph embedding. In 7 simple steps. | by Andy Greatorex
30 July 2020, Towards Data Science

Compose for JanusGraph arrives on Bluemix
15 September 2017, ibm.com

Nordstrom Builds Flexible Backend Ops with Kubernetes, Spark and JanusGraph
3 October 2019, The New Stack

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

Present your product here