DBMS > Apache Druid vs. Riak KV vs. Riak TS vs. Sqrrl vs. ToroDB

System Properties Comparison Apache Druid vs. Riak KV vs. Riak TS vs. Sqrrl vs. ToroDB

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Distributed, fault tolerant key-value store

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

Adaptable, secure NoSQL built on Apache Accumulo

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

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

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Document store

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

druid.apache.org

sqrrl.com

github.com/torodb/server

Technical documentation

druid.apache.org/docs/latest/design

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

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

Developer

Apache Software Foundation and contributors

OpenSource, formerly Basho Technologies

Open Source, formerly Basho Technologies

Amazon

originally Sqrrl Data, Inc.

8Kdata

Initial release

2012

2009

2015

2012

2016

Current release

29.0.1, April 2024

3.2.0, December 2022

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache version 2, commercial enterprise edition

Open Source

commercial

Open Source

AGPL-V3

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

Java

Erlang

Java

Server operating systems

Linux
OS X
Unix

Linux
OS X

Linux

All OS with a Java 7 VM

Data scheme

yes

schema-less columns are supported

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

SQL for querying

yes, limited

APIs and other access methods

JDBC
RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

Clojure
JavaScript
PHP
Python
R
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

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

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

no "single point of failure"

Sharding

making use of Hadoop

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor

making use of Hadoop

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

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

links between datasets can be stored

Transaction concepts

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

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

yes, using Riak Security

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

Access rights for users and roles

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