DBMS > Dragonfly vs. OrientDB vs. Riak TS vs. Snowflake

System Properties Comparison Dragonfly vs. OrientDB vs. Riak TS vs. Snowflake

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Editorial information provided by DB-Engines

Name

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

Multi-model DBMS (Document, Graph, Key/Value)

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

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

Primary database model

Key-value store

Document store
Graph DBMS
Key-value store

Time Series DBMS

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	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

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

orientdb.org

www.snowflake.com

Technical documentation

www.dragonflydb.io/docs

www.orientdb.com/docs/last/index.html

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

docs.snowflake.net/manuals/index.html

Developer

DragonflyDB team and community contributors

OrientDB LTD; CallidusCloud; SAP

Open Source, formerly Basho Technologies

Snowflake Computing Inc.

Initial release

2023

2010

2015

2014

Current release

1.0, March 2023

3.2.29, March 2024

3.0.0, September 2022

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache version 2

Open Source

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

C++

Java

Erlang

Server operating systems

Linux

All OS with a Java JDK (>= JDK 6)

Linux
OS X

hosted

Data scheme

scheme-free

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

yes

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

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.

yes

Secondary indexes

yes

restricted

SQL

Support of SQL

SQL-like query language, no joins

yes, limited

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

CLI Client
JDBC
ODBC

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

Java, Javascript

Erlang

user defined functions

Triggers

publish/subscribe channels provide some trigger functionality

Hooks

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

links between datasets can be stored

yes

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

Access rights for users and roles; record level security configurable

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

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