DBMS > BigchainDB vs. GeoMesa vs. Google BigQuery

System Properties Comparison BigchainDB vs. GeoMesa vs. Google BigQuery

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Editorial information provided by DB-Engines

Name

Description

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Large scale data warehouse service with append-only tables

Primary database model

Document store

Spatial DBMS

Relational DBMS

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

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	0.81
Rank	#214	Overall
	#4	Spatial DBMS

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Website

www.bigchaindb.com

www.geomesa.org

cloud.google.com/bigquery

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.geomesa.org/documentation/stable/user/index.html

cloud.google.com/bigquery/docs

Developer

CCRi and others

Google

Initial release

2016

2014

2010

Current release

4.0.5, February 2024

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache License 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Python

Scala

Server operating systems

Linux

hosted

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
RESTful HTTP API

RESTful HTTP/JSON API

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

depending on storage layer

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

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

depending on storage layer

User concepts

Access control

yes

depending on the DBMS used for storage

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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