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. Bangdb vs. Newts vs. Solr

System Properties Comparison Amazon Neptune vs. Bangdb vs. Newts vs. Solr

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonBangdb  Xexclude from comparisonNewts  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudConverged and high performance database for device data, events, time series, document and graphTime Series DBMS based on CassandraA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelGraph DBMS
RDF store
Document store
Graph DBMS
Time Series DBMS
Time Series DBMSSearch engine
Secondary database modelsSpatial DBMSSpatial 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
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­neptunebangdb.comopennms.github.io/­newtssolr.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.bangdb.comgithub.com/­OpenNMS/­newts/­wikisolr.apache.org/­resources.html
DeveloperAmazonSachin Sinha, BangDBOpenNMS GroupApache Software Foundation
Initial release2017201220142006
Current releaseBangDB 2.0, October 20219.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoBSD 3Open Source infoApache 2.0Open Source infoApache Version 2
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, C++JavaJava
Server operating systemshostedLinuxLinux
OS X
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyesyes infosupports customizable data types and automatic typing
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.nononoyes
Secondary indexesnoyes infosecondary, composite, nested, reverse, geospatialnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoSQL like support with command line toolnoSolr Parallel SQL Interface
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Proprietary protocol
RESTful HTTP API
HTTP REST
Java API
Java API
RESTful HTTP/JSON API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Java
Python
Java.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnononoJava plugins
Triggersnoyes, Notifications (with Streaming only)noyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmSharding infobased on CassandraSharding
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 factor, Knob for CAP (enterprise version only)selectable replication factor infobased on Cassandrayes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable consistency, set CAP knob accordinglyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyes, implements WAL (Write ahead log) as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modenoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yes (enterprise version only)noyes

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 NeptuneBangdbNewtsSolr
DB-Engines blog posts

Elasticsearch replaced Solr as the most popular search engine
12 January 2016, Paul Andlinger

Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

show all

Recent citations in the news

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

Analyze large amounts of graph data to get insights and find trends with Amazon Neptune Analytics | Amazon Web ...
29 November 2023, AWS Blog

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

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

Create a Virtual Knowledge Graph with Amazon Neptune and an Amazon S3 data lake | Amazon Web Services
21 February 2024, AWS Blog

provided by Google News

Farewell, Froggy: The Age of Ribbit Is Nearing an End
25 May 2013, Mother Jones

provided by Google News

SOLR-led walkout demands better conditions for Compass workers
27 February 2024, Daily Northwestern

(SOLR) Technical Pivots with Risk Controls
28 April 2024, Stock Traders Daily

Best Practices from Rackspace for Modernizing a Legacy HBase/Solr Architecture Using AWS Services | Amazon Web ...
9 October 2023, AWS Blog

SOLR hosts teach-in of labor movements at Northwestern
28 January 2024, Daily Northwestern

Top 5 stock gainers and losers: SOLR.V, GRSL.V, ANON.C
21 November 2023, Equity.Guru

provided by Google News



Share this page

Featured Products

SingleStore logo

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

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.

RaimaDB logo

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

Milvus logo

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

Present your product here