DBMS > GeoMesa vs. HarperDB vs. Oracle Berkeley DB vs. PostGIS

System Properties Comparison GeoMesa vs. HarperDB vs. Oracle Berkeley DB vs. PostGIS

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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.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Widely used in-process key-value store

Spatial extension of PostgreSQL

Primary database model

Spatial DBMS

Document store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

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

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Website

www.geomesa.org

www.harperdb.io

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

postgis.net

Technical documentation

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

docs.harperdb.io/docs

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

postgis.net/documentation

Developer

CCRi and others

HarperDB

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2014

2017

1994

2005

Current release

5.0.0, May 2024

3.1, August 2021

18.1.40, May 2020

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free community edition available

Open Source

commercial license available

Open Source

GPL v2.0

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

Node.js

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

Server operating systems

Linux
OS X

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

yes

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON data types

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

only with the Berkeley DB XML edition

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like data manipulation statements

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Supported programming languages

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

.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

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

user defined functions

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

A table resides as a whole on one (or more) nodes in a cluster

none

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

the nodes on which a table resides can be defined

Source-replica replication

yes

based on PostgreSQL

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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 and roles

yes

based on PostgreSQL

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More resources

DB-Engines blog posts

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