DBMS > Axibase vs. Hawkular Metrics vs. Heroic vs. ObjectBox

System Properties Comparison Axibase vs. Hawkular Metrics vs. Heroic vs. ObjectBox

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Primary database model

Time Series DBMS

Object oriented DBMS
Vector DBMS

Secondary database models

Time Series DBMS

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

Score	0.21
Rank	#308	Overall
	#25	Time Series DBMS

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Website

axibase.com/docs/atsd/finance

www.hawkular.org

github.com/spotify/heroic

github.com/objectbox
objectbox.io

Technical documentation

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

spotify.github.io/heroic

docs.objectbox.io

Developer

Axibase Corporation

Community supported by Red Hat

Spotify

ObjectBox Limited

Initial release

2013

2014

2017

Current release

15585

4.0 (May 2024)

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache 2.0

Open Source

Apache 2.0

Bindings are released under Apache 2.0

Apache License 2.0

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

C and C++

Server operating systems

Linux

Linux
OS X
Windows

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

yes, plus "flex" map-like types

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

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

HTTP REST

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Proprietary native API

Supported programming languages

Go
Java
PHP
Python
R
Ruby

Go
Java
Python
Ruby

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

yes

Data sync between devices allowing occasional connected databases to work completely offline

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

yes

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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