DBMS > BigObject vs. Citus vs. Lovefield vs. OpenTSDB vs. SQLite

System Properties Comparison BigObject vs. Citus vs. Lovefield vs. OpenTSDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Embeddable relational database for web apps written in pure JavaScript

Scalable Time Series DBMS based on HBase

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

bigobject.io

www.citusdata.com

google.github.io/lovefield

opentsdb.net

www.sqlite.org

Technical documentation

docs.bigobject.io

docs.citusdata.com

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

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

www.sqlite.org/docs.html

Developer

BigObject, Inc.

Google

currently maintained by Yahoo and other contributors

Dwayne Richard Hipp

Initial release

2015

2010

2014

2011

2000

Current release

8.1, December 2018

2.1.12, February 2017

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

AGPL, commercial license also available

Open Source

Apache 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

JavaScript

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

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

tested with Chrome, Firefox, IE, Safari

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.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

standard, with numerous extensions

SQL-like query language

via JavaScript builder pattern

yes

SQL-92 is not fully supported

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

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

HTTP API
Telnet API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript

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

Lua

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

other methods possible by using 3rd party extensions

none

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

none

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.