DBMS > Blueflood vs. Graph Engine vs. KairosDB vs. Sadas Engine vs. Sqrrl

System Properties Comparison Blueflood vs. Graph Engine vs. KairosDB vs. Sadas Engine vs. Sqrrl

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

Scalable TimeSeries DBMS based on Cassandra

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Distributed Time Series DBMS based on Cassandra or H2

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Time Series DBMS

Graph DBMS
Key-value store

Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

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

Score	0.06
Rank	#352	Overall
	#36	Time Series DBMS

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.60
Rank	#238	Overall
	#20	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

blueflood.io

www.graphengine.io

github.com/kairosdb/kairosdb

www.sadasengine.com

sqrrl.com

Technical documentation

github.com/rax-maas/blueflood/wiki

www.graphengine.io/docs/manual

kairosdb.github.io

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Rackspace

Microsoft

SADAS s.r.l.

Amazon

originally Sqrrl Data, Inc.

Initial release

2013

2010

2013

2006

2012

Current release

1.2.2, November 2018

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MIT License

Open Source

Apache 2.0

commercial

free trial version available

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

Java

.NET and C

Java

C++

Java

Server operating systems

Linux
OS X

.NET

Linux
OS X
Windows

AIX
Linux
Windows

Linux

Data scheme

predefined scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST

RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

JDBC
ODBC
Proprietary protocol

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

C#
C++
F#
Visual Basic

Java
JavaScript

Node.js
PHP
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

Actionscript
C

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

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

Sharding

based on Cassandra

horizontal partitioning

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

based on Cassandra

none

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

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

Foreign keys

Referential integrity

yes

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

simple password-based access control

Access rights for users, groups and roles according to SQL-standard

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

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