DBMS > Badger vs. searchxml vs. Snowflake vs. Tibero

System Properties Comparison Badger vs. searchxml vs. Snowflake vs. Tibero

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Editorial information provided by DB-Engines

Name

Description

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

DBMS for structured and unstructured content wrapped with an application server

Cloud-based data warehousing service for structured and semi-structured data

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Key-value store

Native XML DBMS
Search engine

Relational DBMS

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

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	0.00
Rank	#385	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	1.46
Rank	#151	Overall
	#70	Relational DBMS

Website

github.com/dgraph-io/badger

www.searchxml.net/category/products

www.snowflake.com

us.tmaxsoft.com/products/tibero

Technical documentation

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

www.searchxml.net/support/handouts

docs.snowflake.net/manuals/index.html

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

DGraph Labs

informationpartners gmbh

Snowflake Computing Inc.

TmaxSoft

Initial release

2017

2015

2014

2003

Current release

1.0

7, September 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

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

C++

C and Assembler

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Windows

hosted

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

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

yes

APIs and other access methods

RESTful HTTP API
WebDAV
XQuery
XSLT

CLI Client
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

C++

most other programming languages supported via APIs

JavaScript (Node.js)
Python

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

on the application server

user defined functions

Persistent Stored Procedure (PSM)

Triggers

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

sychronisation to multiple collections

yes

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

multiple readers, single writer

ACID

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.

planned for next version

User concepts

Access control

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

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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