DBMS > CockroachDB vs. Hawkular Metrics vs. Lovefield vs. TimescaleDB vs. TimesTen

System Properties Comparison CockroachDB vs. Hawkular Metrics vs. Lovefield vs. TimescaleDB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

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

Embeddable relational database for web apps written in pure JavaScript

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

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Relational DBMS

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.cockroachlabs.com

www.hawkular.org

google.github.io/lovefield

www.timescale.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

www.cockroachlabs.com/docs

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

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.timescale.com

docs.oracle.com/database/timesten-18.1

Developer

Cockroach Labs

Community supported by Red Hat

Google

Timescale

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2015

2014

2017

1998

Current release

23.1.1, May 2023

2.1.12, February 2017

2.13.0, November 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache 2.0

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

JavaScript

Server operating systems

Linux
macOS
Windows

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes

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

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

SQL-like query language

via JavaScript builder pattern

yes

full PostgreSQL SQL syntax

yes

APIs and other access methods

JDBC

HTTP REST

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

Go
Java
Python
Ruby

JavaScript

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

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

PL/SQL

Triggers

yes

via Hawkular Alerting

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

based on Cassandra

none

yes, across time and space (hash partitioning) attributes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

selectable replication factor

based on Cassandra

none

Source-replica replication with hot standby and reads on replicas

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

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

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More resources

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