DBMS > Drizzle vs. Firebase Realtime Database vs. GreptimeDB vs. Hazelcast vs. Linter

System Properties Comparison Drizzle vs. Firebase Realtime Database vs. GreptimeDB vs. Hazelcast vs. Linter

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

A widely adopted in-memory data grid

RDBMS for high security requirements

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Spatial DBMS

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Website

firebase.google.com/products/realtime-database

greptime.com

hazelcast.com

linter.ru

Technical documentation

firebase.google.com/docs/database

docs.greptime.com

hazelcast.org/imdg/docs

Developer

Drizzle project, originally started by Brian Aker

Google

acquired by Google 2014

Greptime Inc.

Hazelcast

relex.ru

Initial release

2008

2012

2022

2008

1990

Current release

7.2.4, September 2012

5.3.6, November 2023

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available

commercial

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

C++

Rust

Java

C and C++

Server operating systems

FreeBSD
Linux
OS X

hosted

Android
Docker
FreeBSD
Linux
macOS
Windows

All OS with a Java VM

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Data scheme

yes

schema-free

schema-free, schema definition possible

schema-free

yes

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-like query language

yes

APIs and other access methods

JDBC

Android
iOS
JavaScript API
RESTful HTTP API

gRPC
HTTP API
JDBC

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

C
C++
Java
PHP

Java
JavaScript
Objective-C

C++
Erlang
Go
Java
JavaScript

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Python

yes

Event Listeners, Executor Services

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

hooks for callbacks inside the server can be used.

Callbacks are triggered when data changes

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Replicated Map

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

one or two-phase-commit; repeatable reads; read commited

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes, based on authentication and database rules

Simple rights management via user accounts

Role-based access control

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...
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Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
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Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
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Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
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Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
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Licensing and pricing models

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

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