DBMS > Dragonfly vs. Drizzle vs. Riak TS vs. YDB

System Properties Comparison Dragonfly vs. Drizzle vs. Riak TS vs. YDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Key-value store

Relational DBMS

Time Series DBMS

Document store
Relational DBMS

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

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

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

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

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

www.dragonflydb.io/docs

www.tiot.jp/riak-docs/riak/ts/latest

ydb.tech/en/docs

Developer

DragonflyDB team and community contributors

Drizzle project, originally started by Brian Aker

Open Source, formerly Basho Technologies

Yandex

Initial release

2023

2008

2015

2019

Current release

1.0, March 2023

7.2.4, September 2012

3.0.0, September 2022

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

GNU GPL

Open Source

Apache 2.0; commercial license 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

C++

Erlang

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux
OS X

Linux

Data scheme

scheme-free

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

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

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

restricted

yes

SQL

Support of SQL

yes

with proprietary extensions

yes, limited

SQL-like query language (YQL)

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC

HTTP API
Native Erlang Interface

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

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

C
C++
Java
PHP

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

Lua

Erlang

Triggers

publish/subscribe channels provide some trigger functionality

hooks for callbacks inside the server can be used.

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

selectable replication factor

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

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

User concepts

Access control

Password-based authentication

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights defined for Yandex Cloud users

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More resources

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