DBMS > Atos Standard Common Repository vs. Microsoft Azure Cosmos DB vs. Sqrrl vs. Typesense

System Properties Comparison Atos Standard Common Repository vs. Microsoft Azure Cosmos DB vs. Sqrrl vs. Typesense

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Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

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

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Globally distributed, horizontally scalable, multi-model database service

Adaptable, secure NoSQL built on Apache Accumulo

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Document store
Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Search engine

Secondary database models

Spatial DBMS

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

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.80
Rank	#209	Overall
	#14	Search engines

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

azure.microsoft.com/services/cosmos-db

sqrrl.com

typesense.org

Technical documentation

learn.microsoft.com/azure/cosmos-db

typesense.org/docs

Developer

Atos Convergence Creators

Microsoft

Amazon

originally Sqrrl Data, Inc.

Initial release

2016

2014

2012

2015

Current release

1703

License

Commercial or Open Source

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

Linux

hosted

Linux

Data scheme

Schema and schema-less with LDAP views

schema-free

pre-defined schema optional

Typing

predefined data types such as float or date

optional

yes

JSON types

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.

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

LDAP

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

RESTful HTTP API

Supported programming languages

All languages with LDAP bindings

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Actionscript
C

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

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Implicit feature of the cloud service

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

making use of Hadoop

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

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

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

Multi-item ACID transactions with snapshot isolation within a partition

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.

yes

User concepts

Access control

LDAP bind authentication

Access rights can be defined down to the item level

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

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