DBMS > Hawkular Metrics vs. KeyDB vs. Oracle Coherence vs. TimescaleDB vs. XTDB

System Properties Comparison Hawkular Metrics vs. KeyDB vs. Oracle Coherence vs. TimescaleDB vs. XTDB

Editorial information provided by DB-Engines

Name

Description

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

Oracles in-memory data grid solution

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Relational DBMS

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.hawkular.org

github.com/Snapchat/KeyDB
keydb.dev

www.oracle.com/java/coherence

www.timescale.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

docs.keydb.dev

docs.oracle.com/en/middleware/standalone/coherence

docs.timescale.com

www.xtdb.com/docs

Developer

Community supported by Red Hat

EQ Alpha Technology Ltd.

Oracle

Timescale

Juxt Ltd.

Initial release

2014

2019

2007

2017

2019

Current release

14.1, August 2023

2.15.0, May 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD-3

commercial

Open Source

Apache 2.0

Open Source

MIT License

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++

Java

Clojure

Server operating systems

Linux
OS X
Windows

Linux

All OS with a Java VM

Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

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

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

yes, extensible-data-notation format

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

yes

SQL

Support of SQL

yes

full PostgreSQL SQL syntax

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP REST

Proprietary protocol

RESP - REdis Serialization Protoco

JCache
JPA
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST
JDBC

Supported programming languages

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

.Net
C++
Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Clojure
Java

Server-side scripts

Stored procedures

Lua

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

via Hawkular Alerting

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

yes, across time and space (hash partitioning) attributes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

yes, with selectable consistency level

Source-replica replication with hot standby and reads on replicas

yes, each node contains all data

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

Eventual Consistency
Immediate Consistency

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

configurable

ACID

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

optionally

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

authentification to access the cache via certificates or http basic authentication

fine grained access rights according to SQL-standard

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