DBMS > BigchainDB vs. Google Cloud Bigtable vs. Greenplum vs. SQLite vs. TinkerGraph

System Properties Comparison BigchainDB vs. Google Cloud Bigtable vs. Greenplum vs. SQLite vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

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

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.

Widely used embeddable, in-process RDBMS

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Document store

Key-value store
Wide column store

Relational DBMS

Graph DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

www.bigchaindb.com

cloud.google.com/bigtable

greenplum.org

www.sqlite.org

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

bigchaindb.readthedocs.io/en/latest

cloud.google.com/bigtable/docs

docs.greenplum.org

www.sqlite.org/docs.html

Developer

Google

Pivotal Software Inc.

Dwayne Richard Hipp

Initial release

2016

2015

2005

2000

2009

Current release

7.0.0, September 2023

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

Apache 2.0

Open Source

Public Domain

Open Source

Apache 2.0

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

Python

Java

Server operating systems

Linux

hosted

Linux

server-less

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.

yes

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

APIs and other access methods

CLI Client
RESTful HTTP API

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

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

TinkerPop 3

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

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

C
Java
Perl
Python
R

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

Groovy
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

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

Source-replica replication

none

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

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

optional

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 based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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