DBMS > Drizzle vs. Riak KV vs. ScyllaDB vs. XTDB

System Properties Comparison Drizzle vs. Riak KV vs. ScyllaDB vs. XTDB

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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

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

Distributed, fault tolerant key-value store

Cassandra and DynamoDB compatible wide column store

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Wide column store

Document store

Secondary database models

Key-value store

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

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.scylladb.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

docs.scylladb.com

www.xtdb.com/docs

Developer

Drizzle project, originally started by Brian Aker

OpenSource, formerly Basho Technologies

ScyllaDB

Juxt Ltd.

Initial release

2008

2009

2015

2019

Current release

7.2.4, September 2012

3.2.0, December 2022

ScyllaDB Open Source 5.4.1, January 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache version 2, commercial enterprise edition

Open Source

Open Source (AGPL), commercial license available

Open Source

MIT License

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.

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Implementation language

C++

Erlang

C++

Clojure

Server operating systems

FreeBSD
Linux
OS X

Linux
OS X

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

cluster global secondary indices

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements (CQL)

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC

HTTP API
Native Erlang Interface

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

HTTP REST
JDBC

Supported programming languages

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

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

Clojure
Java

Server-side scripts

Stored procedures

Erlang

yes, Lua

Triggers

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

no "single point of failure"

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

in-memory tables

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes, using Riak Security

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more

Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
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