DBMS > Databend vs. Geode vs. Sadas Engine vs. SWC-DB

System Properties Comparison Databend vs. Geode vs. Sadas Engine vs. SWC-DB

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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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

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

geode.apache.org

www.sadasengine.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.databend.com

geode.apache.org/docs

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

Developer

Databend Labs

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

SADAS s.r.l.

Alex Kashirin

Initial release

2021

2002

2006

2020

Current release

1.0.59, April 2023

1.1, February 2017

8.0

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

free trial version available

Open Source

GPL V3

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

Java

C++

Server operating systems

hosted
Linux
macOS

All OS with a Java VM

the JDK (8 or later) is also required

AIX
Linux
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (OQL)

yes

SQL-like query language

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

JDBC
ODBC
Proprietary protocol

Proprietary protocol
Thrift

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

.Net
All JVM based languages
C++
Groovy
Java
Scala

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

C++

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

yes, on a single node

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

managed by 'Learn by Usage'

User concepts

Access control

Users with fine-grained authorization concept, user roles

Access rights per client and object definable

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

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