DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon DynamoDB vs. jBASE vs. Spark SQL vs. TigerGraph

System Properties Comparison Amazon DynamoDB vs. jBASE vs. Spark SQL vs. TigerGraph

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonjBASE  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudA robust multi-value DBMS comprising development tools and middlewareSpark SQL is a component on top of 'Spark Core' for structured data processingA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument store
Key-value store
Multivalue DBMSRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score77.57
Rank#16  Overall
#2  Document stores
#2  Key-value stores
Score1.43
Rank#160  Overall
#3  Multivalue DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score1.83
Rank#141  Overall
#13  Graph DBMS
Websiteaws.amazon.com/­dynamodbwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasespark.apache.org/­sqlwww.tigergraph.com
Technical documentationdocs.aws.amazon.com/­dynamodbdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9spark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.com
DeveloperAmazonRocket Software (formerly Zumasys)Apache Software Foundation
Initial release2012199120142017
Current release5.73.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercialOpen Source infoApache 2.0commercial
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 languageScalaC++
Server operating systemshostedAIX
Linux
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesoptionalyesyes
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.yesnono
Secondary indexesyesno
SQL infoSupport of SQLnoEmbedded SQL for jBASE in BASICSQL-like DML and DDL statementsSQL-like query language (GSQL)
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
Basic
Jabbascript
Java
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnoyesnoyes
Triggersyes infoby integration with AWS Lambdayesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Foreign keys infoReferential integritynononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoACID across one or more tables within a single AWS account and regionACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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)Access rights can be defined down to the item levelnoRole-based access control

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
3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
» more

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

More resources
Amazon DynamoDBjBASESpark SQLTigerGraph
DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Increased popularity for consuming DBMS services out of the cloud
2 October 2015, Paul Andlinger

show all

Recent citations in the news

AWS announces Amazon DynamoDB zero-ETL integration with Amazon OpenSearch Service
28 November 2023, AWS Blog

Simplify cross-account access control with Amazon DynamoDB using resource-based policies | Amazon Web Services
20 March 2024, AWS Blog

A new and improved AWS CDK construct for Amazon DynamoDB tables | Amazon Web Services
31 January 2024, AWS Blog

Bulk update Amazon DynamoDB tables with AWS Step Functions | Amazon Web Services
20 March 2024, AWS Blog

Simplify private connectivity to Amazon DynamoDB with AWS PrivateLink | Amazon Web Services
19 March 2024, AWS Blog

provided by Google News

Temenos signs first customer in India
24 August 2009, Finextra

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

1.5 Years of Spark Knowledge in 8 Tips | by Michael Berk
23 December 2023, Towards Data Science

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

provided by Google News

New TigerGraph CEO Refocuses Efforts on Enterprise Customers
31 July 2023, Datanami

TigerGraph update adds enterprise-scale capabilities
31 October 2023, TechTarget

Aerospike takes on Neo4j and TigerGraph with launch of graph database
20 June 2023, SiliconANGLE News

TigerGraph partners with Pascal as master distributor for APJ region
10 January 2024, VnExpress International

Graph Database Market worth $7.3 billion by 2028 - Exclusive Report by MarketsandMarkets™
30 August 2023, PR Newswire

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

Neo4j logo

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

SingleStore logo

The database to transact, analyze and contextualize your data in real time.
Try it today.

Ontotext logo

GraphDB allows you to link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs. Get it 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

Present your product here