DBMS > etcd vs. Google Cloud Firestore vs. GreptimeDB vs. Hypertable vs. Sadas Engine

System Properties Comparison etcd vs. Google Cloud Firestore vs. GreptimeDB vs. Hypertable vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

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

An open source BigTable implementation based on distributed file systems such as Hadoop

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

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

Score	7.05
Rank	#53	Overall
	#5	Key-value stores

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	0.09
Rank	#343	Overall
	#31	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

etcd.io
github.com/etcd-io/etcd

firebase.google.com/products/firestore

greptime.com

www.sadasengine.com

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

firebase.google.com/docs/firestore

docs.greptime.com

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Google

Greptime Inc.

Hypertable Inc.

SADAS s.r.l.

Initial release

2017

2022

2009

2006

Current release

3.4, August 2019

0.9.8.11, March 2016

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

Open Source

GNU version 3. Commercial license available

commercial

free trial version 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

C++

Server operating systems

FreeBSD
Linux
Windows

experimental

hosted

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

an inofficial Windows port is available

AIX
Linux
Windows

Data scheme

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.

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

APIs and other access methods

gRPC
JSON over HTTP

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

gRPC
HTTP API
JDBC

C++ API
Thrift

JDBC
ODBC
Proprietary protocol

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C++
Erlang
Go
Java
JavaScript

C++
Java
Perl
PHP
Python
Ruby

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Python

Triggers

yes, watching key changes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Multi-source replication

selectable replication factor on file system level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

managed by 'Learn by Usage'

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Simple rights management via user accounts

Access rights for users, groups and roles 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

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

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12 December 2019, Paul Andlinger

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