DBMS > Hawkular Metrics vs. Hypertable vs. STSdb vs. SurrealDB

System Properties Comparison Hawkular Metrics vs. Hypertable vs. STSdb vs. SurrealDB

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

An open source BigTable implementation based on distributed file systems such as Hadoop

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Time Series DBMS

Wide column store

Key-value store

Document store
Graph DBMS

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Website

www.hawkular.org

github.com/STSSoft/STSdb4

surrealdb.com

Technical documentation

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

surrealdb.com/docs

Developer

Community supported by Red Hat

Hypertable Inc.

STS Soft SC

SurrealDB Ltd

Initial release

2014

2009

2011

2022

Current release

0.9.8.11, March 2016

4.0.8, September 2015

v1.5.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU version 3. Commercial license available

Open Source

GPLv2, commercial license available

Open Source

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++

Rust

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Windows

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

restricted

only exact value or prefix value scans

SQL

Support of SQL

SQL-like query language

APIs and other access methods

HTTP REST

C++ API
Thrift

.NET Client API

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

Go
Java
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

C#
Java

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

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

selectable replication factor

based on Cassandra

selectable replication factor on file system level

none

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

Immediate Consistency

Foreign keys

Referential integrity

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, based on authentication and database rules

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