DBMS > DolphinDB vs. Greenplum vs. GreptimeDB vs. VoltDB

System Properties Comparison DolphinDB vs. Greenplum vs. GreptimeDB vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

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.

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

Technical documentation

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

docs.greenplum.org

docs.greptime.com

docs.voltdb.com

Developer

DolphinDB, Inc

Pivotal Software Inc.

Greptime Inc.

VoltDB Inc.

Initial release

2018

2005

2022

2010

Current release

v2.00.4, January 2022

7.0.0, September 2023

11.3, April 2022

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Rust

Java, C++

Server operating systems

Linux
Windows

Linux

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X

for development

Data scheme

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

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

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

only a subset of SQL 99

APIs and other access methods

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

JDBC
ODBC

gRPC
HTTP API
JDBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

C
Java
Perl
Python
R

C++
Erlang
Go
Java
JavaScript

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Python

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication
Source-replica replication

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

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

Administrators, Users, Groups

fine grained access rights according to SQL-standard

Simple rights management via user accounts

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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