DBMS > ArcadeDB vs. etcd vs. FeatureBase vs. H2

System Properties Comparison ArcadeDB vs. etcd vs. FeatureBase vs. H2

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Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

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

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	0.22
Rank	#309	Overall
	#139	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Website

arcadedb.com

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

www.featurebase.com

www.h2database.com

Technical documentation

docs.arcadedb.com

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

docs.featurebase.com

www.h2database.com/html/main.html

Developer

Arcade Data

Molecula and Pilosa Open Source Contributors

Thomas Mueller

Initial release

2021

2017

2005

Current release

September 2021

3.4, August 2019

2022, May 2022

2.2.220, July 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

Open Source

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

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

All OS with a Java VM

FreeBSD
Linux
Windows

experimental

Linux
macOS

All OS with a Java VM

Data scheme

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

SQL

Support of SQL

SQL-like query language, no joins

SQL queries

yes

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

gRPC
JSON over HTTP

gRPC
JDBC
Kafka Connector
ODBC

JDBC
ODBC

Supported programming languages

Java

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

Java
Python

Java

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

yes, using Linux fsync

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

fine grained access rights according to SQL-standard

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