DBMS > Atos Standard Common Repository vs. Heroic vs. HyperSQL vs. KeyDB vs. SwayDB

System Properties Comparison Atos Standard Common Repository vs. Heroic vs. HyperSQL vs. KeyDB vs. SwayDB

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

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Document store
Key-value store

Time Series DBMS

Relational DBMS

Key-value store

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

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

github.com/spotify/heroic

hsqldb.org

github.com/Snapchat/KeyDB
keydb.dev

swaydb.simer.au

Technical documentation

spotify.github.io/heroic

hsqldb.org/web/hsqlDocsFrame.html

docs.keydb.dev

Developer

Atos Convergence Creators

Spotify

EQ Alpha Technology Ltd.

Simer Plaha

Initial release

2016

2014

2001

2019

2018

Current release

1703

2.7.2, June 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

based on BSD license

Open Source

BSD-3

Open Source

GNU Affero GPL V3.0

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++

Scala

Server operating systems

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

schema-free

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

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

via Elasticsearch

yes

by using the Redis Search module

SQL

Support of SQL

yes

APIs and other access methods

LDAP

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

HTTP API

JDBC via HTTP
JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

Supported programming languages

All languages with LDAP bindings

All languages supporting JDBC/ODBC
Java

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

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Java, SQL

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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
Immediate Consistency

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Optimistic locking, atomic execution of commands blocks and scripts

Atomic execution of operations

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

fine grained access rights according to SQL-standard

simple password-based access control and ACL

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