DBMS > Bangdb vs. BoltDB vs. Hawkular Metrics vs. NSDb vs. SAP IQ

System Properties Comparison Bangdb vs. BoltDB vs. Hawkular Metrics vs. NSDb vs. SAP IQ

Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

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.

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

Columnar RDBMS optimized for Big Data analytics

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store

Time Series DBMS

Relational DBMS

column-oriented

Secondary database models

Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Website

bangdb.com

github.com/boltdb/bolt

www.hawkular.org

nsdb.io

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

docs.bangdb.com

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

nsdb.io/Architecture

help.sap.com/docs/SAP_IQ

Developer

Sachin Sinha, BangDB

Community supported by Red Hat

SAP, formerly Sybase

Initial release

2012

2013

2014

2017

1994

Current release

BangDB 2.0, October 2021

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

BSD 3

Open Source

MIT License

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

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

C, C++

Java

Java, Scala

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

all fields are automatically indexed

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HTTP REST

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
C#
C++
Java
Python

Go
Java
Python
Ruby

Java
Scala

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Sharding

based on Cassandra

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

none

selectable replication factor

based on Cassandra

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

none

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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, run db with in-memory only mode

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

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