DBMS > Heroic vs. Oracle Rdb vs. Sequoiadb vs. Sqrrl

System Properties Comparison Heroic vs. Oracle Rdb vs. Sequoiadb vs. Sqrrl

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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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

NewSQL database with distributed OLTP and SQL

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Time Series DBMS

Relational DBMS

Document store
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	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

github.com/spotify/heroic

www.oracle.com/database/technologies/related/rdb.html

www.sequoiadb.com

sqrrl.com

Technical documentation

spotify.github.io/heroic

www.oracle.com/database/technologies/related/rdb-doc.html

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Spotify

Oracle, originally developed by Digital Equipment Corporation (DEC)

Sequoiadb Ltd.

Amazon

originally Sqrrl Data, Inc.

Initial release

2014

1984

2013

2012

Current release

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Server: AGPL; Client: Apache V2

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

C++

Java

Server operating systems

HP Open VMS

Linux

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

via Elasticsearch

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

proprietary protocol using JSON

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

.Net
C++
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

JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

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
Immediate Consistency

Immediate Consistency

Eventual Consistency

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

yes, on a single node

Document is locked during a transaction

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

simple password-based access control

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

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