DBMS > Google Cloud Bigtable vs. Greenplum vs. Postgres-XL vs. SQLite vs. YottaDB

System Properties Comparison Google Cloud Bigtable vs. Greenplum vs. Postgres-XL vs. SQLite vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

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.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Widely used embeddable, in-process RDBMS

A fast and solid embedded Key-value store

Primary database model

Key-value store
Wide column store

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

Relational DBMS

using the Octo plugin

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

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

cloud.google.com/bigtable

Technical documentation

cloud.google.com/bigtable/docs

docs.greenplum.org

www.postgres-xl.org/documentation

www.sqlite.org/docs.html

yottadb.com/resources/documentation

Developer

Google

Pivotal Software Inc.

Dwayne Richard Hipp

YottaDB, LLC

Initial release

2015

2005

2014

since 2012, originally named StormDB

2000

2001

Current release

7.0.0, September 2023

10 R1, October 2018

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Mozilla public license

Open Source

Public Domain

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Server operating systems

hosted

Linux

Linux
macOS

server-less

Docker
Linux

Data scheme

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

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

since Version 4.2

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

SQL-92 is not fully supported

by using the Octo plugin

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JDBC
ODBC

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
Python

C
Java
Perl
Python
R

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

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

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

MVCC

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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