DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. DolphinDB vs. EJDB vs. Pinecone

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. DolphinDB vs. EJDB vs. Pinecone

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Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

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.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

A managed, cloud-native vector database

Primary database model

Secondary database models

Relational DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.dolphindb.com

github.com/Softmotions/ejdb

www.pinecone.io

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

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

github.com/Softmotions/ejdb/blob/master/README.md

docs.pinecone.io/docs/overview

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

DolphinDB, Inc

Softmotions

Pinecone Systems, Inc

Initial release

2016

2018

2012

2019

Current release

v2.00.4, January 2022

License

Commercial or Open Source

commercial

free community version available

Open Source

GPLv2

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

C++

Server operating systems

hosted

Linux
Windows

server-less

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

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

in-process shared library

RESTful HTTP API

Supported programming languages

C
Java
Perl
Python
R

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

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

fine grained access rights according to SQL-standard

Administrators, Users, Groups

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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