DBMS > Databend vs. Lovefield vs. MonetDB vs. OpenTSDB vs. SQLite

System Properties Comparison Databend vs. Lovefield vs. MonetDB vs. OpenTSDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Embeddable relational database for web apps written in pure JavaScript

A relational database management system that stores data in columns

Scalable Time Series DBMS based on HBase

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

github.com/datafuselabs/databend
www.databend.com

google.github.io/lovefield

www.monetdb.org

opentsdb.net

www.sqlite.org

Technical documentation

docs.databend.com

github.com/google/lovefield/blob/master/docs/spec_index.md

www.monetdb.org/Documentation

opentsdb.net/docs/build/html/index.html

www.sqlite.org/docs.html

Developer

Databend Labs

Google

MonetDB BV

currently maintained by Yahoo and other contributors

Dwayne Richard Hipp

Initial release

2021

2014

2004

2011

2000

Current release

1.0.59, April 2023

2.1.12, February 2017

Dec2023 (11.49), December 2023

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Mozilla Public License 2.0

Open Source

LGPL

Open Source

Public Domain

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

Rust

JavaScript

Java

Server operating systems

hosted
Linux
macOS

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

yes

not rigid because of 'dynamic typing' concept.

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

SQL 2003 with some extensions

yes

SQL-92 is not fully supported

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP API
Telnet API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

JavaScript

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

Erlang
Go
Java
Python
R
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes, in SQL, C, R

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding via remote tables

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

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