DBMS > BigObject vs. Greenplum vs. Lovefield vs. TimescaleDB

System Properties Comparison BigObject vs. Greenplum vs. Lovefield vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Embeddable relational database for web apps written in pure JavaScript

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

bigobject.io

greenplum.org

google.github.io/lovefield

www.timescale.com

Technical documentation

docs.bigobject.io

docs.greenplum.org

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

docs.timescale.com

Developer

BigObject, Inc.

Pivotal Software Inc.

Google

Timescale

Initial release

2015

2005

2014

2017

Current release

7.0.0, September 2023

2.1.12, February 2017

2.15.0, May 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache 2.0

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

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
OS X
Windows

Data scheme

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

since Version 4.2

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language

via JavaScript builder pattern

yes

full PostgreSQL SQL syntax

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC

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

Supported programming languages

C
Java
Perl
Python
R

JavaScript

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Lua

yes

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

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

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

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

User concepts

Access control

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

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RSA: EMC integrates Hadoop with Greenplum database
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Greenplum 6 ventures outside the analytic box
19 March 2019, ZDNet

Greenplum 6 review: Jack of all trades, master of some
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4 April 2024, PR Newswire

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18 March 2019, azure.microsoft.com

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

Timescale announces $15M investment and new enterprise version of TimescaleDB
29 January 2019, TechCrunch

provided by Google News

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