DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon DynamoDB vs. Cubrid vs. DolphinDB vs. jBASE vs. Kinetica

System Properties Comparison Amazon DynamoDB vs. Cubrid vs. DolphinDB vs. jBASE vs. Kinetica

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonCubrid  Xexclude from comparisonDolphinDB  Xexclude from comparisonjBASE  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.A robust multi-value DBMS comprising development tools and middlewareFully vectorized database across both GPUs and CPUs
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMSMultivalue DBMSRelational DBMS
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.45
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websiteaws.amazon.com/­dynamodbcubrid.com (korean)
cubrid.org (english)
www.dolphindb.comwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.kinetica.com
Technical documentationdocs.aws.amazon.com/­dynamodbcubrid.org/­manualsdocs.dolphindb.cn/­en/­help200/­index.htmldocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.kinetica.com
DeveloperAmazonCUBRID Corporation, CUBRID FoundationDolphinDB, IncRocket Software (formerly Zumasys)Kinetica
Initial release20122008201819912012
Current release11.0, January 2021v2.00.4, January 20225.77.1, August 2021
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoApache Version 2.0commercial infofree community version availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++, JavaC++C, C++
Server operating systemshostedLinux
Windows
Linux
Windows
AIX
Linux
Windows
Linux
Data schemeschema-freeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesoptionalyes
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.nonoyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoyesSQL-like query languageEmbedded SQL for jBASE in BASICSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
OLE DB
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
.Net
Basic
Jabbascript
Java
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoJava Stored Proceduresyesyesuser defined functions
Triggersyes infoby integration with AWS Lambdayesnoyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyesyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnonoyes
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 regionACIDyesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes infoGPU vRAM or System RAM
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-standardAdministrators, Users, GroupsAccess rights can be defined down to the item levelAccess rights for users and roles on table level

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 DynamoDBCubridDolphinDBjBASEKinetica
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

Use Amazon DynamoDB incremental exports to drive continuous data retention | Amazon Web Services
12 June 2024, AWS Blog

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

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

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

provided by Google News

Temenos signs first customer in India
24 August 2009, Finextra

provided by Google News

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

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.

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