DBMS > Atos Standard Common Repository vs. BigchainDB vs. Google BigQuery vs. InterSystems Caché vs. KeyDB

System Properties Comparison Atos Standard Common Repository vs. BigchainDB vs. Google BigQuery vs. InterSystems Caché vs. KeyDB

Editorial information provided by DB-Engines

Name

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

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Large scale data warehouse service with append-only tables

A multi-model DBMS and application server

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Primary database model

Document store
Key-value store

Document store

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Key-value store

Secondary database models

Document store

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Website

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

www.bigchaindb.com

cloud.google.com/bigquery

www.intersystems.com/products/cache

github.com/Snapchat/KeyDB
keydb.dev

Technical documentation

bigchaindb.readthedocs.io/en/latest

cloud.google.com/bigquery/docs

docs.intersystems.com

docs.keydb.dev

Developer

Atos Convergence Creators

Google

InterSystems

EQ Alpha Technology Ltd.

Initial release

2016

2010

1997

2019

Current release

1703

2018.1.4, May 2020

License

Commercial or Open Source

commercial

Open Source

AGPL v3

commercial

Open Source

BSD-3

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

Python

C++

Server operating systems

Linux

hosted

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

depending on used data model

schema-free

Typing

predefined data types such as float or date

optional

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

SQL

Support of SQL

yes

APIs and other access methods

LDAP

CLI Client
RESTful HTTP API

RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protoco

Supported programming languages

All languages with LDAP bindings

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Java

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

Since BigQuery is designed for querying data

ACID

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

yes

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users, groups and roles

simple password-based access control and ACL

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