DBMS > HarperDB vs. Newts vs. Oracle Berkeley DB vs. Sequoiadb

System Properties Comparison HarperDB vs. Newts vs. Oracle Berkeley DB vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

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.

Time Series DBMS based on Cassandra

Widely used in-process key-value store

NewSQL database with distributed OLTP and SQL

Primary database model

Document store

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store
Relational DBMS

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

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

www.harperdb.io

opennms.github.io/newts

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

www.sequoiadb.com

Technical documentation

docs.harperdb.io/docs

github.com/OpenNMS/newts/wiki

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

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

HarperDB

OpenNMS Group

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Sequoiadb Ltd.

Initial release

2017

2014

1994

2013

Current release

3.1, August 2021

18.1.40, May 2020

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

commercial license available

Open Source

Server: AGPL; Client: Apache V2

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

Node.js

Java

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

C++

Server operating systems

Linux
OS X

Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

Data scheme

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

yes

oid, date, timestamp, binary, regex

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

SQL-like data manipulation statements

yes

SQL interfaced based on SQLite is available

SQL-like query language

APIs and other access methods

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

HTTP REST
Java API

proprietary protocol using JSON

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

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

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

JavaScript

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

based on Cassandra

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using LMDB

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles

simple password-based access control

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