DBMS > EsgynDB vs. GreptimeDB vs. HyperSQL vs. Oracle NoSQL

System Properties Comparison EsgynDB vs. GreptimeDB vs. HyperSQL vs. Oracle NoSQL

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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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

www.esgyn.cn

greptime.com

hsqldb.org

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

docs.greptime.com

hsqldb.org/web/hsqlDocsFrame.html

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Esgyn

Greptime Inc.

Oracle

Initial release

2015

2022

2001

2011

Current release

2.7.2, June 2023

23.3, December 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

based on BSD license

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

Server operating systems

Linux

Android
Docker
FreeBSD
Linux
macOS
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
Solaris SPARC/x86

Data scheme

yes

schema-free, schema definition possible

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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 DML and DDL statements

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC
HTTP API
JDBC

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C++
Erlang
Go
Java
JavaScript

All languages supporting JDBC/ODBC
Java

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Python

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

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

off heap cache

User concepts

Access control

fine grained access rights according to SQL-standard

Simple rights management via user accounts

fine grained access rights according to SQL-standard

Access rights for users and roles

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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