DBMS > EsgynDB vs. GreptimeDB vs. PostGIS vs. Transwarp ArgoDB vs. VoltDB

System Properties Comparison EsgynDB vs. GreptimeDB vs. PostGIS vs. Transwarp ArgoDB vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

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

Spatial extension of PostgreSQL

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

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

Search engine

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.12
Rank	#348	Overall
	#151	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

www.esgyn.cn

greptime.com

postgis.net

www.transwarp.cn/en/product/argodb

www.voltdb.com

Technical documentation

docs.greptime.com

postgis.net/documentation

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

docs.voltdb.com

Developer

Esgyn

Greptime Inc.

Transwarp

VoltDB Inc.

Initial release

2015

2022

2005

2010

Current release

3.4.2, February 2024

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPL v2.0

commercial

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++, Java

Rust

Java, C++

Server operating systems

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

Secondary indexes

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC
HTTP API
JDBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C++
Erlang
Go
Java
JavaScript

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Python

user defined functions

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

based on PostgreSQL

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

based on PostgreSQL

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

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.

User concepts

Access control

fine grained access rights according to SQL-standard

Simple rights management via user accounts

yes

based on PostgreSQL

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.

Related products and services

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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