DBMS > Databend vs. EJDB vs. Graph Engine vs. HyperSQL

System Properties Comparison Databend vs. EJDB vs. Graph Engine vs. HyperSQL

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Editorial information provided by DB-Engines

Name

Description

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

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Primary database model

Relational DBMS

Document store

Graph DBMS
Key-value store

Relational DBMS

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Website

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

github.com/Softmotions/ejdb

www.graphengine.io

hsqldb.org

Technical documentation

docs.databend.com

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

www.graphengine.io/docs/manual

hsqldb.org/web/hsqlDocsFrame.html

Developer

Databend Labs

Softmotions

Microsoft

Initial release

2021

2012

2010

2001

Current release

1.0.59, April 2023

2.7.2, June 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GPLv2

Open Source

MIT License

Open Source

based on BSD license

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

Rust

.NET and C

Java

Server operating systems

hosted
Linux
macOS

server-less

.NET

All OS with a Java VM

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

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

in-process shared library

RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

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

C#
C++
F#
Visual Basic

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

yes

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

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