DBMS > GeoMesa vs. Google Cloud Bigtable vs. Oracle NoSQL vs. RocksDB

System Properties Comparison GeoMesa vs. Google Cloud Bigtable vs. Oracle NoSQL vs. RocksDB

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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.

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Spatial DBMS

Key-value store
Wide column store

Document store
Key-value store
Relational DBMS

Key-value store

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

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

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.geomesa.org

cloud.google.com/bigtable

www.oracle.com/database/nosql/technologies/nosql

rocksdb.org

Technical documentation

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

cloud.google.com/bigtable/docs

docs.oracle.com/en/database/other-databases/nosql-database/index.html

github.com/facebook/rocksdb/wiki

Developer

CCRi and others

Google

Oracle

Facebook, Inc.

Initial release

2014

2015

2011

2013

Current release

5.0.0, May 2024

24.1, May 2024

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

BSD

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

C++

Server operating systems

hosted

Linux
Solaris SPARC/x86

Linux

Data scheme

yes

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

Typing

predefined data types such as float or date

yes

optional

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

SQL-like DML and DDL statements

APIs and other access methods

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

RESTful HTTP API

C++ API
Java API

Supported programming languages

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

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

horizontal partitioning

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

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

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)

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

configurable

ACID within a storage node (=shard)

yes

Concurrency

Support for concurrent manipulation of data

yes

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.

depending on storage layer

yes

off heap cache

yes

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)

Access rights for users and roles

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