DBMS > Apache IoTDB vs. Bangdb vs. EXASOL vs. Hawkular Metrics vs. Manticore Search

System Properties Comparison Apache IoTDB vs. Bangdb vs. EXASOL vs. Hawkular Metrics vs. Manticore Search

Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Multi-storage database for search, including full-text search.

Primary database model

Time Series DBMS

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Search engine

Secondary database models

Spatial DBMS

Time Series DBMS

using the Manticore Columnar Library

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Website

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

docs.bangdb.com

www.exasol.com/resources

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

manual.manticoresearch.com

Developer

Apache Software Foundation

Sachin Sinha, BangDB

Exasol

Community supported by Red Hat

Manticore Software

Initial release

2018

2012

2000

2014

2017

Current release

1.1.0, April 2023

BangDB 2.0, October 2021

6.0, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD 3

commercial

Open Source

Apache 2.0

Open Source

GPL version 2

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

C, C++

Java

C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

Data scheme

yes

schema-free

yes

schema-free

Fixed schema

Typing

predefined data types such as float or date

yes

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

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

SQL like support with command line tool

yes

SQL-like query language

APIs and other access methods

JDBC
Native API

Proprietary protocol
RESTful HTTP API

.Net
JDBC
ODBC
WebSocket

HTTP REST

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
C#
C++
Java
Python

Java
Lua
Python
R

Go
Java
Python
Ruby

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

yes, Notifications (with Streaming only)

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

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

Sharding

based on Cassandra

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

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

selectable replication factor

based on Cassandra

Synchronous replication based on Galera library

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

The original contents of fields are not stored in the Manticore index.

In-memory capabilities

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

yes

yes, run db with in-memory only mode

yes

User concepts

Access control

yes

yes (enterprise version only)

Access rights for users, groups and roles according to SQL-standard

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