DBMS > DolphinDB vs. Hawkular Metrics vs. TimescaleDB vs. Warp 10

System Properties Comparison DolphinDB vs. Hawkular Metrics vs. TimescaleDB vs. Warp 10

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	4.23
Rank	#82	Overall
	#6	Time Series DBMS

Score	0.04
Rank	#374	Overall
	#38	Time Series DBMS

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Score	0.08
Rank	#358	Overall
	#35	Time Series DBMS

Website

Technical documentation

docs.dolphindb.cn/en/help200/index.html

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

docs.timescale.com

www.warp10.io/content/02_Getting_started

Developer

DolphinDB, Inc

Community supported by Red Hat

Timescale

SenX

Initial release

2018

2014

2017

2015

Current release

v2.00.4, January 2022

2.13.0, November 2023

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache License 2.0

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

C++

Java

Server operating systems

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

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

SQL-like query language

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

HTTP REST

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

HTTP API
Jupyter
WebSocket

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

Go
Java
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

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

yes

WarpScript

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on Cassandra

yes, across time and space (hash partitioning) attributes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Source-replica replication with hot standby and reads on replicas

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Administrators, Users, Groups

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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… • DEVCLASS
5 June 2019, DevClass

provided by Google News

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

Visualizing IoT Data at Scale With Hopara and TimescaleDB
16 May 2023, Embedded Computing Design

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft

SQL and TimescaleDB. This article takes a closer look into… | by Alibaba Cloud
31 July 2019, DataDrivenInvestor

provided by Google News

Star Trek: 5 Things Picard Does Better Than Discovery (& 5 Things Discovery Does Better)
4 April 2020, Screen Rant

Launched Just A Year Ago, Open-Source Scality S3 Server Gains Extraordinary Momentum As It Simplifies The Life Of ...
28 June 2017, PR Newswire UK

Time Series Databases Software market latest trends, CAGR, and forecast till 2026 | eSherpa Market Reports
13 April 2020, openPR

provided by Google News

Share this page