DBMS > Apache Impala vs. ArcadeDB vs. EJDB vs. Newts vs. OrigoDB

System Properties Comparison Apache Impala vs. ArcadeDB vs. EJDB vs. Newts vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Time Series DBMS based on Cassandra

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Document store

Time Series DBMS

Document store
Object oriented DBMS

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

impala.apache.org

arcadedb.com

github.com/Softmotions/ejdb

opennms.github.io/newts

origodb.com

Technical documentation

impala.apache.org/impala-docs.html

docs.arcadedb.com

github.com/Softmotions/ejdb/blob/master/README.md

github.com/OpenNMS/newts/wiki

origodb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Arcade Data

Softmotions

OpenNMS Group

Robert Friberg et al

Initial release

2013

2021

2012

2014

2009

under the name LiveDB

Current release

4.1.0, June 2022

September 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

GPLv2

Open Source

Apache 2.0

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

Linux

All OS with a Java VM

server-less

Linux
OS X
Windows

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language, no joins

APIs and other access methods

JDBC
ODBC

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

in-process shared library

HTTP REST
Java API

.NET Client API
HTTP API
LINQ

Supported programming languages

All languages supporting JDBC/ODBC

Java

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Java

.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

none

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

relationship in graphs

typically not needed, however similar functionality with collection joins possible

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

Write ahead log

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 rights for users, groups and roles

based on Apache Sentry and Kerberos

Role based authorization

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More resources

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provided by Google News

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