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. IBM Db2 warehouse vs. Spark SQL vs. SWC-DB

System Properties Comparison Amazon Neptune vs. IBM Db2 warehouse vs. Spark SQL vs. SWC-DB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudCloud-based data warehousing serviceSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMS
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSWide column store
Secondary database modelsTime Series 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
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websiteaws.amazon.com/­neptunewww.ibm.com/­products/­db2/­warehousespark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonIBMApache Software FoundationAlex Kashirin
Initial release2017201420142020
Current release3.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC++
Server operating systemshostedhostedLinux
OS X
Windows
Linux
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes
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 infoImport/export of XML data possiblenono
Secondary indexesnoyesno
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
.NET Client API
JDBC
ODBC
OLE DB
JDBC
ODBC
Proprietary protocol
Thrift
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Java
Python
R
Scala
C++
Server-side scripts infoStored proceduresnoPL/SQL, SQL PLnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark CoreSharding
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.yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardno

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 NeptuneIBM Db2 warehouse infoformerly named IBM dashDBSpark SQLSWC-DB infoSuper Wide Column Database
Recent citations in the news

Amazon Neptune Analytics is now available in the AWS Europe (London) Region
14 March 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 1: Full-text search | Amazon Web ...
7 May 2024, 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

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

provided by Google News

Introducing the next generation of Db2 Warehouse: Our cost-effective, cloud-native data warehouse built for always-on ...
11 July 2023, ibm.com

Db2 Warehouse delivers 4x faster query performance than previously, while cutting storage costs by 34x
11 July 2023, ibm.com

Top 7 Cloud Data Warehouse Companies
31 May 2023, Datamation

Announcing the availability of Bring-Your-Own-License and Reserved Instance plans for next generation Db2 ...
7 August 2023, ibm.com

Data mining in Db2 Warehouse: the basics
23 June 2020, Towards Data Science

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

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

provided by Google News

2022 All O-Zone Football Team
17 December 2022, Ozarks Sports Zone

provided by Google News



Share this page

Featured Products

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.

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.

Present your product here