DBMS > atoti vs. Badger vs. searchxml

System Properties Comparison atoti vs. Badger vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Object oriented DBMS

Key-value store

Native XML DBMS
Search engine

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

Score	0.84
Rank	#233	Overall
	#11	Object oriented DBMS

Score	0.13
Rank	#371	Overall
	#57	Key-value stores

Score	0.00
Rank	#389	Overall
	#7	Native XML DBMS
	#26	Search engines

Website

www.atoti.io

github.com/dgraph-io/badger

www.searchxml.net/category/products

Technical documentation

godoc.org/github.com/dgraph-io/badger

www.searchxml.net/support/handouts

Developer

ActiveViam

DGraph Labs

informationpartners gmbh

Initial release

2017

2015

Current release

1.0

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache 2.0

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++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Windows

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

APIs and other access methods

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

Python

yes

on the application server

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

Domain, group and role-based access control at the document level and for application services

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