DBMS > Databend vs. Lovefield vs. openGemini vs. Sadas Engine

System Properties Comparison Databend vs. Lovefield vs. openGemini vs. Sadas Engine

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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 relational database for web apps written in pure JavaScript

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	0.28
Rank	#287	Overall
	#131	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

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

google.github.io/lovefield

www.opengemini.org
github.com/openGemini

www.sadasengine.com

Technical documentation

docs.databend.com

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.opengemini.org/guide

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Databend Labs

Google

Huawei and openGemini community

SADAS s.r.l.

Initial release

2021

2014

2022

2006

Current release

1.0.59, April 2023

2.1.12, February 2017

1.1, July 2023

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

free trial version available

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

JavaScript

C++

Server operating systems

hosted
Linux
macOS

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
Windows

AIX
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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

SQL-like query language

via JavaScript builder pattern

SQL-like query language

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

HTTP REST

JDBC
ODBC
Proprietary protocol

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

JavaScript

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

managed by 'Learn by Usage'

User concepts

Access control

Users with fine-grained authorization concept, user roles

Administrators and common users accounts

Access rights for users, groups and roles according to SQL-standard

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