DBMS > Apache Phoenix vs. etcd vs. Google Cloud Firestore vs. Memgraph vs. SQLite

System Properties Comparison Apache Phoenix vs. etcd vs. Google Cloud Firestore vs. Memgraph vs. SQLite

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

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 graph database built for real-time streaming and compatible with Neo4j

Widely used embeddable, in-process RDBMS

Primary database model

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

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

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	3.19
Rank	#94	Overall
	#8	Graph DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

phoenix.apache.org

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

firebase.google.com/products/firestore

memgraph.com

www.sqlite.org

Technical documentation

phoenix.apache.org

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

firebase.google.com/docs/firestore

memgraph.com/docs

www.sqlite.org/docs.html

Social network pages

Developer

Apache Software Foundation

Google

Memgraph Ltd

Dwayne Richard Hipp

Initial release

2014

2017

2000

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

3.4, August 2019

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

Open Source

BSL 1.1; commercial license for enterprise edition available

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

Server operating systems

Linux
Unix
Windows

FreeBSD
Linux
Windows

experimental

hosted

Linux

server-less

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

schema-free and schema-optional

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC

gRPC
JSON over HTTP

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

Bolt protocol
Cypher query language

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

.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
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

yes, Firebase Rules & Cloud Functions

Triggers

yes, watching key changes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

dynamic graph partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

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

Multi-source replication

Multi-source replication using RAFT

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

ACID

yes

ACID

with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

Durability

Support for making data persistent

yes

with periodic snapshot and write-ahead logging (WAL) of changes

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

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

Users, roles and permissions

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
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Licensing and pricing models

You can check out our pricing model and licenses on the company website .
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