DBMS > GeoMesa vs. Google Cloud Bigtable vs. Immudb vs. NSDb

System Properties Comparison GeoMesa vs. Google Cloud Bigtable vs. Immudb vs. NSDb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

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

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Spatial DBMS

Key-value store
Wide column store

Key-value store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

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

Score	0.24
Rank	#305	Overall
	#43	Key-value stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

www.geomesa.org

cloud.google.com/bigtable

github.com/codenotary/immudb
immudb.io

nsdb.io

Technical documentation

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

cloud.google.com/bigtable/docs

docs.immudb.io

nsdb.io/Architecture

Developer

CCRi and others

Google

Codenotary

Initial release

2014

2015

2020

2017

Current release

4.0.5, February 2024

1.2.3, April 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 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

Scala

Java, Scala

Server operating systems

hosted

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

SQL-like syntax

SQL-like query language

APIs and other access methods

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

gRPC protocol
PostgreSQL wire protocol

gRPC
HTTP REST
WebSocket

Supported programming languages

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

.Net
Go
Java
JavaScript (Node.js)
Python

Java
Scala

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

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

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

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

Durability

Support for making data persistent

yes

Using Apache Lucene

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

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

What is Google Bigtable? | Definition from TechTarget
1 March 2022, TechTarget

Google announces Axion, its first Arm-based CPU for data centers
9 April 2024, Yahoo Movies Canada

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

Codenotary Releases immudb v1.9DOM
19 October 2023, Business Wire

Codenotary brings its immutable database to the cloud
21 June 2023, TechCrunch

Codenotary launches cloud version of tamper-proof database
27 June 2023, SC Media

A Step by Step Guide to immudb — the open source immutable database
18 May 2020, hackernoon.com

Immudb: Open-source database, built on a zero trust model
17 December 2021, Help Net Security

provided by Google News

Share this page