DBMS > DolphinDB vs. Graph Engine vs. Heroic vs. TimescaleDB vs. Warp 10

System Properties Comparison DolphinDB vs. Graph Engine vs. Heroic vs. TimescaleDB vs. Warp 10

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.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

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

Graph DBMS
Key-value store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	1.65
Rank	#140	Overall
	#9	Time Series DBMS

Score	0.91
Rank	#184	Overall
	#16	Graph DBMS
	#30	Key-value stores

Score	0.22
Rank	#285	Overall
	#25	Time Series DBMS

Score	4.70
Rank	#83	Overall
	#5	Time Series DBMS

Score	0.18
Rank	#291	Overall
	#26	Time Series DBMS

Website

www.dolphindb.com

www.graphengine.io

spotify.github.io/heroic/#!/index

www.timescale.com

www.warp10.io

Technical documentation

www.dolphindb.com/help

www.graphengine.io/docs/manual

spotify.github.io/heroic/#!/docs/overview

docs.timescale.com

www.warp10.io/content/02_Getting_started

Developer

DolphinDB, Inc

Microsoft

Spotify

Timescale

SenX

Initial release

2018

2010

2014

2017

2015

Current release

v2.00.4, January 2022

2.6.0, February 2022

License

Commercial or Open Source

commercial

free community version available

Open Source

MIT License

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++

.NET and C

Java

Server operating systems

Linux
Windows

.NET

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

via Elasticsearch

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

RESTful HTTP API

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

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

C#
C++
F#
Visual Basic

.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

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes, across time and space (hash partitioning) attributes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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
Immediate Consistency

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Specific characteristics

Timescale is the creator of TimescaleDB , the first open-source relational database...
» more

Competitive advantages

TimescaleDB is purpose-built to scale and handle time-series data workloads and is...
» more

Typical application scenarios

Time-series Analytics TimescaleDB boosts the performance of PostgreSQL for time-series...
» more

Key customers

TransferWise, Maersk, Walmart, Comcast, LaunchDarkly, IBM, NOV, Cisco, Nutanix, Warner...
» more

Market metrics

With over 12,700 GitHub stars and growing, 1,000,000 active databases, and an active...
» more

Licensing and pricing models

TimescaleDB is available as a self-hosted product under two licenses, the Timescale...
» more

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

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More resources

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