DBMS > atoti vs. Hawkular Metrics vs. JSqlDb vs. KeyDB vs. LeanXcale

System Properties Comparison atoti vs. Hawkular Metrics vs. JSqlDb vs. KeyDB vs. LeanXcale

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

JavaScript Query Language Database, stores JavaScript objects and primitives

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Primary database model

Object oriented DBMS

Time Series DBMS

Document store
Object oriented DBMS

Key-value store

Key-value store
Relational DBMS

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

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

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Website

atoti.io

www.hawkular.org

jsqldb.org (offline)

github.com/Snapchat/KeyDB
keydb.dev

www.leanxcale.com

Technical documentation

docs.atoti.io

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

docs.keydb.dev

Developer

ActiveViam

Community supported by Red Hat

Konrad von Backstrom

EQ Alpha Technology Ltd.

LeanXcale

Initial release

2014

2018

2019

2015

Current release

0.8, December 2018

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache 2.0

Open Source

BSD-3

commercial

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
OS X
Windows

Linux
macOS
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

by using the Redis Search module

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

through Apache Derby

APIs and other access methods

HTTP REST

Proprietary protocol

RESP - REdis Serialization Protoco

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

Go
Java
Python
Ruby

JavaScript

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
Scala

Server-side scripts

Stored procedures

Python

functions in JavaScript

Lua

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

based on Cassandra

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

using RocksDB

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

simple password-based access control and ACL

More information provided by the system vendor

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