DBMS > BigObject vs. DuckDB vs. MarkLogic vs. MySQL vs. Tkrzw

System Properties Comparison BigObject vs. DuckDB vs. MarkLogic vs. MySQL vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Operational and transactional Enterprise NoSQL database

Widely used open source RDBMS

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Key/Value like access via memcached API

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

bigobject.io

duckdb.org

www.progress.com/marklogic

www.mysql.com

dbmx.net/tkrzw

Technical documentation

docs.bigobject.io

duckdb.org/docs

www.progress.com/marklogic/documentation

dev.mysql.com/doc

Developer

BigObject, Inc.

MarkLogic Corp.

Oracle

since 2010, originally MySQL AB, then Sun

Mikio Hirabayashi

Initial release

2015

2018

2001

1995

2020

Current release

1.0.0, June 2024

11.0, December 2022

8.4.0, April 2024

0.9.3, August 2020

License

Commercial or Open Source

commercial

free community edition available

Open Source

MIT License

commercial

restricted free version is available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

C++

C and C++

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

server-less

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS

Data scheme

yes

schema-free

Schema can be enforced

yes

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

SQL-like DML and DDL statements

yes

SQL92

yes

with proprietary extensions

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Lua

yes

via XQuery or JavaScript

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

can act as a resource manager in an XA/JTA transaction

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

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

yes, with Range Indexes

yes

using specific database classes

User concepts

Access control

Role-based access control at the document and subdocument levels

Users with fine-grained authorization concept

no user groups or roles

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