DBMS > Amazon DynamoDB vs. Databend vs. DolphinDB vs. EsgynDB vs. Pinecone

System Properties Comparison Amazon DynamoDB vs. Databend vs. DolphinDB vs. EsgynDB vs. Pinecone

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

DolphinDB 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.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A managed, cloud-native vector database

Primary database model

Document store
Key-value store

Secondary database models

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	3.23
Rank	#92	Overall
	#2	Vector DBMS

Website

aws.amazon.com/dynamodb

github.com/datafuselabs/databend
www.databend.com

www.dolphindb.com

www.esgyn.cn

www.pinecone.io

Technical documentation

docs.aws.amazon.com/dynamodb

docs.databend.com

docs.dolphindb.cn/en/help200/index.html

docs.pinecone.io/docs/overview

Developer

Amazon

Databend Labs

DolphinDB, Inc

Esgyn

Pinecone Systems, Inc

Initial release

2012

2021

2018

2015

2019

Current release

1.0.59, April 2023

v2.00.4, January 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

commercial

free community version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Rust

C++

C++, Java

Server operating systems

hosted

hosted
Linux
macOS

Linux
Windows

Linux

hosted

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

CLI Client
JDBC
RESTful HTTP API

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

ADO.NET
JDBC
ODBC

RESTful HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python
Rust

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

All languages supporting JDBC/ODBC/ADO.Net

Python

Server-side scripts

Stored procedures

yes

Java Stored Procedures

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Multi-source replication between multi datacenters

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID across one or more tables within a single AWS account and region

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Users with fine-grained authorization concept, user roles

Administrators, Users, Groups

fine grained access rights according to SQL-standard

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