DBMS > Blueflood vs. GeoMesa vs. HyperSQL vs. Oracle Berkeley DB

System Properties Comparison Blueflood vs. GeoMesa vs. HyperSQL vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Widely used in-process key-value store

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

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

Website

blueflood.io

www.geomesa.org

hsqldb.org

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

Technical documentation

github.com/rax-maas/blueflood/wiki

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

hsqldb.org/web/hsqlDocsFrame.html

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

Developer

Rackspace

CCRi and others

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2013

2014

2001

1994

Current release

5.0.0, May 2024

2.7.2, June 2023

18.1.40, May 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache License 2.0

Open Source

based on BSD license

Open Source

commercial license available

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

Java

Scala

Java

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

Server operating systems

Linux
OS X

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

predefined 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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

APIs and other access methods

HTTP REST

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC
Java

.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

Java, SQL

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

depending on storage layer

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

depending on storage layer

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

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

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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