DBMS > Databend vs. Dragonfly vs. Lovefield vs. Machbase Neo vs. RethinkDB

System Properties Comparison Databend vs. Dragonfly vs. Lovefield vs. Machbase Neo vs. RethinkDB

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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Embeddable relational database for web apps written in pure JavaScript

TimeSeries DBMS for AIoT and BigData

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Website

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

github.com/dragonflydb/dragonfly
www.dragonflydb.io

google.github.io/lovefield

machbase.com

rethinkdb.com

Technical documentation

docs.databend.com

www.dragonflydb.io/docs

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

machbase.com/dbms

rethinkdb.com/docs

Developer

Databend Labs

DragonflyDB team and community contributors

Google

Machbase

The Linux Foundation

since July 2017

Initial release

2021

2023

2014

2013

2009

Current release

1.0.59, April 2023

1.0, March 2023

2.1.12, February 2017

V8.0, August 2023

2.4.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSL 1.1

Open Source

Apache 2.0

commercial

free test version available

Open Source

Apache Version 2

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

C++

JavaScript

C++

Server operating systems

hosted
Linux
macOS

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

scheme-free

yes

schema-free

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

yes

string, binary, float, bool, date, geometry

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

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

JavaScript

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

Lua

Triggers

publish/subscribe channels provide some trigger functionality

Using read-only observers

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Atomic execution of command blocks and scripts

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

MVCC based

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

volatile and lookup table

User concepts

Access control

Users with fine-grained authorization concept, user roles

Password-based authentication

simple password-based access control

yes

users and table-level permissions

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

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