DBMS > Databend vs. FeatureBase vs. Snowflake

System Properties Comparison Databend vs. FeatureBase vs. Snowflake

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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

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

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

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	0.22
Rank	#309	Overall
	#139	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

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

www.featurebase.com

www.snowflake.com

Technical documentation

docs.databend.com

docs.featurebase.com

docs.snowflake.net/manuals/index.html

Developer

Databend Labs

Molecula and Pilosa Open Source Contributors

Snowflake Computing Inc.

Initial release

2021

2017

2014

Current release

1.0.59, April 2023

2022, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Rust

Server operating systems

hosted
Linux
macOS

Linux
macOS

hosted

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

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

SQL

Support of SQL

yes

SQL queries

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

gRPC
JDBC
Kafka Connector
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

Java
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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, using Linux fsync

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

Users with fine-grained authorization concept, user roles and pluggable authentication

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