DBMS > GeoMesa vs. Google Cloud Spanner vs. HEAVY.AI vs. searchxml

System Properties Comparison GeoMesa vs. Google Cloud Spanner vs. HEAVY.AI vs. searchxml

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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.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Spatial DBMS

Relational DBMS

Native XML DBMS
Search engine

Secondary database models

Spatial DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

www.geomesa.org

cloud.google.com/spanner

github.com/heavyai/heavydb
www.heavy.ai

www.searchxml.net/category/products

Technical documentation

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

cloud.google.com/spanner/docs

docs.heavy.ai

www.searchxml.net/support/handouts

Developer

CCRi and others

Google

HEAVY.AI, Inc.

informationpartners gmbh

Initial release

2014

2017

2016

2015

Current release

4.0.5, February 2024

5.10, January 2022

1.0

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Apache Version 2; enterprise edition available

commercial

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++ and CUDA

C++

Server operating systems

hosted

Linux

Windows

Data scheme

yes

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

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
Thrift
Vega

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/Thrift
Python

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

on the application server

Triggers

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Multi-source replication with 3 replicas for regional instances.

Multi-source replication

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

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

multiple readers, single writer

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)

fine grained access rights according to SQL-standard

Domain, group and role-based access control at the document level and for application services

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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