DBMS > FeatureBase vs. GeoMesa vs. Google BigQuery vs. Oracle

System Properties Comparison FeatureBase vs. GeoMesa vs. Google BigQuery vs. Oracle

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Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

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

Large scale data warehouse service with append-only tables

Widely used RDBMS

Primary database model

Relational DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.23
Rank	#296	Overall
	#134	Relational DBMS

Score	0.78
Rank	#214	Overall
	#4	Spatial DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Website

www.featurebase.com

www.geomesa.org

cloud.google.com/bigquery

www.oracle.com/database

Technical documentation

docs.featurebase.com

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

cloud.google.com/bigquery/docs

docs.oracle.com/en/database

Developer

Molecula and Pilosa Open Source Contributors

CCRi and others

Google

Oracle

Initial release

2017

2014

2010

1980

Current release

2022, May 2022

5.0.1, July 2024

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

commercial

restricted free version is available

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 C++

Server operating systems

Linux
macOS

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

yes

Schemaless in JSON and XML columns

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

SQL queries

yes

with proprietary extensions

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

user defined functions

in JavaScript

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Since BigQuery is designed for querying data

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using Linux fsync

yes

In-memory capabilities

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

yes

depending on storage layer

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

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)

fine grained access rights according to SQL-standard

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