DBMS > Firebase Realtime Database vs. Graph Engine vs. GreptimeDB vs. H2 vs. IBM Db2 warehouse

System Properties Comparison Firebase Realtime Database vs. Graph Engine vs. GreptimeDB vs. H2 vs. IBM Db2 warehouse

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.

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

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Cloud-based data warehousing service

Primary database model

Document store

Graph DBMS
Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Website

firebase.google.com/products/realtime-database

www.graphengine.io

greptime.com

www.h2database.com

www.ibm.com/products/db2/warehouse

Technical documentation

firebase.google.com/docs/database

www.graphengine.io/docs/manual

docs.greptime.com

www.h2database.com/html/main.html

Developer

Google

acquired by Google 2014

Microsoft

Greptime Inc.

Thomas Mueller

IBM

Initial release

2012

2010

2022

2005

2014

Current release

2.2.220, July 2023

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache Version 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

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

.NET and C

Rust

Java

Server operating systems

hosted

.NET

Android
Docker
FreeBSD
Linux
macOS
Windows

All OS with a Java VM

hosted

Data scheme

schema-free

yes

schema-free, schema definition possible

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.

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP API

gRPC
HTTP API
JDBC

JDBC
ODBC

.NET Client API
JDBC
ODBC
OLE DB

Supported programming languages

Java
JavaScript
Objective-C

C#
C++
F#
Visual Basic

C++
Erlang
Go
Java
JavaScript

Java

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Python

Java Stored Procedures and User-Defined Functions

PL/SQL, SQL PL

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

yes, multi-version concurrency control (MVCC)

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

yes, based on authentication and database rules

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

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

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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