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. Hypertable vs. OrigoDB vs. Spark SQL

System Properties Comparison Amazon Neptune vs. Hypertable vs. OrigoDB vs. Spark SQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonHypertable  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionFast, reliable graph database built for the cloudAn open source BigTable implementation based on distributed file systems such as HadoopA fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Wide column storeDocument store
Object oriented DBMS
Relational 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
Score0.06
Rank#380  Overall
#50  Document stores
#19  Object oriented DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptuneorigodb.comspark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourcesorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonHypertable Inc.Robert Friberg et alApache Software Foundation
Initial release201720092009 infounder the name LiveDB2014
Current release0.9.8.11, March 20163.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availableOpen SourceOpen 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++C#Scala
Server operating systemshostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoUser defined using .NET types and collectionsyes
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.nono infocan be achieved using .NETno
Secondary indexesnorestricted infoonly exact value or prefix value scansyesno
SQL infoSupport of SQLnononoSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
C++ API
Thrift
.NET Client API
HTTP API
LINQ
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C++
Java
Perl
PHP
Python
Ruby
.NetJava
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesno
Triggersnonoyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
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 on file system levelSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noRole based authorizationno

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 NeptuneHypertableOrigoDBSpark SQL
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

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

SQL and TimescaleDB. This article takes a closer look into… | by Alibaba Cloud
31 July 2019, DataDrivenInvestor

Decorate your Windows XP with Hyperdesk
30 July 2008, CNET

The Collective: Customize Your Computer & Your Phone With Star Trek
18 March 2009, TrekMovie

5 Free NoSQL Database Certification Courses in 2024 – AIM
31 January 2024, Analytics India Magazine

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Performant IPv4 Range Spark Joins | by Jean-Claude Cote
24 January 2024, Towards Data Science

Simba Technologies(R) Introduces New, Powerful JDBC Driver With SQL Connector for Apache Spark(TM)
17 March 2024, Yahoo Singapore News

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

Present your product here