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. Graphite vs. Microsoft Azure Table Storage vs. Sphinx

System Properties Comparison Amazon Neptune vs. Graphite vs. Microsoft Azure Table Storage vs. Sphinx

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGraphite  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudData logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperA Wide Column Store for rapid development using massive semi-structured datasetsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelGraph DBMS
RDF store
Time Series DBMSWide column storeSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score4.83
Rank#67  Overall
#4  Time Series DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score5.95
Rank#55  Overall
#5  Search engines
Websiteaws.amazon.com/­neptunegithub.com/­graphite-project/­graphite-webazure.microsoft.com/­en-us/­services/­storage/­tablessphinxsearch.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesgraphite.readthedocs.iosphinxsearch.com/­docs
DeveloperAmazonChris DavisMicrosoftSphinx Technologies Inc.
Initial release2017200620122001
Current release3.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonC++
Server operating systemshostedLinux
Unix
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesNumeric data onlyyesno
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 indexesnononoyes infofull-text index on all search fields
SQL infoSupport of SQLnononoSQL-like query language (SphinxQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
HTTP API
Sockets
RESTful HTTP APIProprietary protocol
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
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.noneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyes infolockingyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noAccess rights based on private key authentication or shared access signaturesno

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 NeptuneGraphiteMicrosoft Azure Table StorageSphinx
DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

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

show all

Recent citations in the news

Exploring new features of Apache TinkerPop 3.7.x in Amazon Neptune | Amazon Web Services
7 June 2024, AWS Blog

Building NHM London's Planetary Knowledge Base with Amazon Neptune and the Registry of Open Data on AWS ...
5 June 2024, AWS Blog

Unit testing Apache TinkerPop transactions: From TinkerGraph to Amazon Neptune | Amazon Web Services
3 June 2024, AWS Blog

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

provided by Google News

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

The value of time series data and TSDBs
10 June 2021, InfoWorld

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

provided by Google News

Working with Azure to Use and Manage Data Lakes
7 March 2024, Simplilearn

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, hackernoon.com

How to use Azure Table storage in .Net
14 January 2019, InfoWorld

Quick Guide to Azure Storage Pricing
16 May 2023, DevOps.com

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

provided by Google News

Switching From Sphinx to MkDocs Documentation — What Did I Gain and Lose
2 February 2024, Towards Data Science

5 Powerful Alternatives to Elasticsearch
25 April 2024, Insider Monkey

Manticore is a Faster Alternative to Elasticsearch in C++
25 July 2022, hackernoon.com

Royal Mail stamp prices could rise, warns Czech Sphinx
3 June 2024, Proactive Investors UK

Perplexity AI: From Its Use To Operation, Everything You Need To Know About Google's Newest Challenger
11 January 2024, Free Press Journal

provided by Google News



Share this page

Featured Products

Neo4j logo

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

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

Milvus logo

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

Present your product here