DBMS > Firebase Realtime Database vs. GreptimeDB vs. Hawkular Metrics vs. LokiJS vs. MarkLogic

System Properties Comparison Firebase Realtime Database vs. GreptimeDB vs. Hawkular Metrics vs. LokiJS vs. MarkLogic

Editorial information provided by DB-Engines

Name

Description

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

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.

In-memory JavaScript DBMS

Operational and transactional Enterprise NoSQL database

Primary database model

Document store

Time Series DBMS

Document store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Website

firebase.google.com/products/realtime-database

greptime.com

www.hawkular.org

github.com/techfort/LokiJS

www.marklogic.com

Technical documentation

firebase.google.com/docs/database

docs.greptime.com

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

techfort.github.io/LokiJS

docs.marklogic.com

Developer

Google

acquired by Google 2014

Greptime Inc.

Community supported by Red Hat

MarkLogic Corp.

Initial release

2012

2022

2014

2001

Current release

11.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Rust

Java

JavaScript

C++

Server operating systems

hosted

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

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

Linux
OS X
Windows

Data scheme

schema-free

schema-free, schema definition possible

schema-free

Schema can be enforced

Typing

predefined data types such as float or date

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 views

yes

SQL

Support of SQL

yes

SQL92

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

gRPC
HTTP API
JDBC

HTTP REST

JavaScript API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

Supported programming languages

Java
JavaScript
Objective-C

C++
Erlang
Go
Java
JavaScript

Go
Java
Python
Ruby

JavaScript

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Python

View functions in JavaScript

yes

via XQuery or JavaScript

Triggers

Callbacks are triggered when data changes

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

atomic operations within a single collection possible

ACID

can act as a resource manager in an XA/JTA transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

In-memory capabilities

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

yes

yes, with Range Indexes

User concepts

Access control

yes, based on authentication and database rules

Simple rights management via user accounts

Role-based access control at the document and subdocument levels

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.

Related products and services

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More resources

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