DBMS > BigchainDB vs. Hive vs. MonetDB vs. SAP HANA vs. TimescaleDB

System Properties Comparison BigchainDB vs. Hive vs. MonetDB vs. SAP HANA vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A relational database management system that stores data in columns

In-memory, column based data store. Available as appliance or cloud service

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Document store

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Relational DBMS

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Trend Chart

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

www.bigchaindb.com

hive.apache.org

www.monetdb.org

www.sap.com/products/hana.html

www.timescale.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

cwiki.apache.org/confluence/display/Hive/Home

www.monetdb.org/Documentation

help.sap.com/hana

docs.timescale.com

Developer

Apache Software Foundation

initially developed by Facebook

MonetDB BV

SAP

Timescale

Initial release

2016

2012

2004

2010

2017

Current release

3.1.3, April 2022

Dec2023 (11.49), December 2023

2.0 SPS07 (April 4, 2023), April 2023

2.15.0, May 2024

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache Version 2

Open Source

Mozilla Public License 2.0

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Python

Java

Server operating systems

Linux

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

SQL 2003 with some extensions

yes

full PostgreSQL SQL syntax

APIs and other access methods

CLI Client
RESTful HTTP API

JDBC
ODBC
Thrift

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C++
Java
PHP
Python

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes, in SQL, C, R

SQLScript, R

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

yes

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Source-replica replication available in experimental status

yes

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

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

yes

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

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