DBMS > Dragonfly vs. GreptimeDB vs. Hawkular Metrics vs. Postgres-XL

System Properties Comparison Dragonfly vs. GreptimeDB vs. Hawkular Metrics vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

An open source Time Series DBMS built for increased scalability, high performance and efficiency

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.44
Rank	#255	Overall
	#38	Key-value stores

Score	0.09
Rank	#343	Overall
	#31	Time Series DBMS

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Website

github.com/dragonflydb/dragonfly
www.dragonflydb.io

greptime.com

www.hawkular.org

www.postgres-xl.org

Technical documentation

www.dragonflydb.io/docs

docs.greptime.com

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

www.postgres-xl.org/documentation

Developer

DragonflyDB team and community contributors

Greptime Inc.

Community supported by Red Hat

Initial release

2023

2022

2014

since 2012, originally named StormDB

Current release

1.0, March 2023

10 R1, October 2018

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Mozilla public 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

C++

Rust

Java

Server operating systems

Linux

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Linux
macOS

Data scheme

scheme-free

schema-free, schema definition possible

schema-free

yes

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

gRPC
HTTP API
JDBC

HTTP REST

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

Supported programming languages

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

C++
Erlang
Go
Java
JavaScript

Go
Java
Python
Ruby

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

Lua

Python

user defined functions

Triggers

publish/subscribe channels provide some trigger functionality

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

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

Password-based authentication

Simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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