DBMS > Atos Standard Common Repository vs. Hawkular Metrics vs. KeyDB vs. STSdb

System Properties Comparison Atos Standard Common Repository vs. Hawkular Metrics vs. KeyDB vs. STSdb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Key-value store

Time Series DBMS

Key-value store

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

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	0.63
Rank	#232	Overall
	#32	Key-value stores

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.hawkular.org

github.com/Snapchat/KeyDB
keydb.dev

github.com/STSSoft/STSdb4

Technical documentation

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

docs.keydb.dev

Developer

Atos Convergence Creators

Community supported by Red Hat

EQ Alpha Technology Ltd.

STS Soft SC

Initial release

2016

2014

2019

2011

Current release

1703

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD-3

Open Source

GPLv2, commercial license available

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++

Server operating systems

Linux

Linux
OS X
Windows

Linux

Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

Typing

predefined data types such as float or date

optional

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes

primitive types and user defined types (classes)

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

by using the Redis Search module

SQL

Support of SQL

APIs and other access methods

LDAP

HTTP REST

Proprietary protocol

RESP - REdis Serialization Protoco

.NET Client API

Supported programming languages

All languages with LDAP bindings

Go
Java
Python
Ruby

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C#
Java

Server-side scripts

Stored procedures

Lua

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

In-memory capabilities

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

yes

User concepts

Access control

LDAP bind authentication

simple password-based access control and ACL

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived…
5 June 2019, DevClass

provided by Google News

Snap snaps up database developer KeyDB to make its infrastructure more snappy
12 May 2022, TechCrunch

Introducing Garnet – an open-source, next-generation, faster cache-store for accelerating applications and services
18 March 2024, microsoft.com

Microsoft open-sources unique “Garnet” cache-store; a Redis rival?
19 March 2024, The Stack

Dragonfly 0.13 Database Adds Experimental SSD-Based Data Tiering, More SIMD Work
2 January 2023, Phoronix

With Indigenous AWS Silicon Plumbed In, Cloud Giant Flexes its Arm (Chips)
12 May 2020, Tech Monitor

provided by Google News

Share this page