DBMS > BoltDB vs. Hawkular Metrics vs. LeanXcale vs. NSDb vs. Oracle Berkeley DB

System Properties Comparison BoltDB vs. Hawkular Metrics vs. LeanXcale vs. NSDb vs. Oracle Berkeley DB

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Widely used in-process key-value store

Primary database model

Key-value store

Time Series DBMS

Key-value store
Relational DBMS

Time Series DBMS

Key-value store

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	0.70
Rank	#225	Overall
	#31	Key-value stores

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	0.28
Rank	#286	Overall
	#41	Key-value stores
	#130	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Website

github.com/boltdb/bolt

www.hawkular.org

www.leanxcale.com

nsdb.io

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

Technical documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

nsdb.io/Architecture

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

Developer

Community supported by Red Hat

LeanXcale

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2013

2014

2015

2017

1994

Current release

18.1.40, May 2020

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

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

Java, Scala

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

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Linux
macOS

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

yes

through Apache Derby

SQL-like query language

yes

SQL interfaced based on SQLite is available

APIs and other access methods

HTTP REST

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

gRPC
HTTP REST
WebSocket

Supported programming languages

Go
Java
Python
Ruby

C
Java
Scala

Java
Scala

.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

Triggers

yes

via Hawkular Alerting

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

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