DBMS > Apache Drill vs. etcd vs. Google Cloud Firestore vs. InfluxDB vs. SAP HANA

System Properties Comparison Apache Drill vs. etcd vs. Google Cloud Firestore vs. InfluxDB vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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.

DBMS for storing time series, events and metrics

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store
Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

drill.apache.org

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

firebase.google.com/products/firestore

www.influxdata.com/products/influxdb-overview

www.sap.com/products/hana.html

Technical documentation

drill.apache.org/docs

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

firebase.google.com/docs/firestore

docs.influxdata.com/influxdb

help.sap.com/hana

Developer

Apache Software Foundation

Google

SAP

Initial release

2012

2017

2013

2010

Current release

1.20.3, January 2023

3.4, August 2019

2.7.6, April 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

Open Source

MIT-License; commercial enterprise version available

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
Windows

experimental

hosted

Linux
OS X

through Homebrew

Appliance or cloud-service

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

gRPC
JSON over HTTP

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

HTTP API
JSON over UDP

JDBC
ODBC

Supported programming languages

C++

.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

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

Server-side scripts

Stored procedures

user defined functions

yes, Firebase Rules & Cloud Functions

SQLScript, R

Triggers

yes, watching key changes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

yes

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

in enterprise version only

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

Depending on used storage engine

yes

User concepts

Access control

Depending on the underlying data source

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

yes

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