DBMS > Quasardb vs. Riak TS vs. Sqrrl vs. VelocityDB

System Properties Comparison Quasardb vs. Riak TS vs. Sqrrl vs. VelocityDB

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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.

Description

Distributed, high-performance timeseries database

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 .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS
Object oriented DBMS

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

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

quasar.ai

sqrrl.com

velocitydb.com

Technical documentation

doc.quasar.ai/master

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

velocitydb.com/UserGuide

Developer

quasardb

Open Source, formerly Basho Technologies

Amazon

originally Sqrrl Data, Inc.

VelocityDB Inc

Initial release

2009

2015

2012

2011

Current release

3.14.1, January 2024

3.0.0, September 2022

7.x

License

Commercial or Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

commercial

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

Java

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X

Linux

Any that supports .NET

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

restricted

yes

SQL

Support of SQL

SQL-like query language

yes, limited

APIs and other access methods

HTTP API

HTTP API
Native Erlang Interface

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

.Net

Supported programming languages

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

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

.Net

Server-side scripts

Stored procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

Sharding

making use of Hadoop

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with selectable replication factor

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

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.

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

ACID

Atomic updates per row, document, or graph entity

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

Cryptographically strong user authentication and audit trail

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

Based on Windows Authentication

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