DBMS > GeoMesa vs. Google Cloud Spanner vs. GridDB vs. Heroic

System Properties Comparison GeoMesa vs. Google Cloud Spanner vs. GridDB vs. Heroic

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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.

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Scalable in-memory time series database optimized for IoT and Big Data

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Primary database model

Spatial DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Key-value store
Relational DBMS

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

Score	0.78
Rank	#214	Overall
	#4	Spatial DBMS

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Website

www.geomesa.org

cloud.google.com/spanner

griddb.net

github.com/spotify/heroic

Technical documentation

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

cloud.google.com/spanner/docs

docs.griddb.net

spotify.github.io/heroic

Developer

CCRi and others

Google

Toshiba Corporation

Spotify

Initial release

2014

2017

2013

2014

Current release

5.0.1, July 2024

5.1, August 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

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

Scala

C++

Java

Server operating systems

hosted

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

via Elasticsearch

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Triggers

yes

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

Multi-source replication with 3 replicas for regional instances.

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

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

ACID

Strict serializable isolation

ACID at container level

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

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 can be defined per database

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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