DBMS > BoltDB vs. Dgraph vs. Hawkular Metrics vs. NSDb vs. PostGIS

System Properties Comparison BoltDB vs. Dgraph vs. Hawkular Metrics vs. NSDb vs. PostGIS

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

Distributed and scalable native Graph DBMS

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

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

Spatial extension of PostgreSQL

Primary database model

Secondary database models

Relational DBMS

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

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Website

github.com/boltdb/bolt

Technical documentation

dgraph.io/docs

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

nsdb.io/Architecture

postgis.net/documentation

Developer

Dgraph Labs, Inc.

Community supported by Red Hat

Initial release

2013

2016

2014

2017

2005

Current release

3.4.2, February 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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

Java

Java, Scala

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

HTTP REST

gRPC
HTTP REST
WebSocket

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Go
Java
Python
Ruby

Java
Scala

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

based on Cassandra

Sharding

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication via Raft

selectable replication factor

based on Cassandra

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate 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.

User concepts

Access control

Planned for future releases

yes

based on PostgreSQL

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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