DBMS > GeoMesa vs. Oracle Berkeley DB vs. RisingWave

System Properties Comparison GeoMesa vs. Oracle Berkeley DB vs. RisingWave

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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.

Widely used in-process key-value store

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Primary database model

Spatial DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	0.64
Rank	#238	Overall
	#110	Relational DBMS

Website

www.geomesa.org

www.oracle.com/database/technologies/related/berkeleydb.html

www.risingwave.com/database

Technical documentation

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

docs.oracle.com/cd/E17076_05/html/index.html

docs.risingwave.com/docs/current/intro

Developer

CCRi and others

Oracle

originally developed by Sleepycat, which was acquired by Oracle

RisingWave Labs

Initial release

2014

1994

2022

Current release

5.0.0, May 2024

18.1.40, May 2020

1.2, September 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

commercial license available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

C, Java, C++ (depending on the Berkeley DB edition)

Rust

Server operating systems

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

JDBC
PostgreSQL wire protocol

Supported programming languages

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

UDFs in Python or Java

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Source-replica replication

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

Foreign keys

Referential integrity

Transaction concepts

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

ACID

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

Users and Roles

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More resources

DB-Engines blog posts

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