DBMS > ArcadeDB vs. BigObject vs. HBase vs. NSDb

System Properties Comparison ArcadeDB vs. BigObject vs. HBase vs. NSDb

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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

Analytic DBMS for real-time computations and queries

Wide-column store based on Apache Hadoop and on concepts of BigTable

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

a hierachical model (tree) can be imposed

Wide column store

Time Series DBMS

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

Score	0.10
Rank	#358	Overall
	#48	Document stores
	#38	Graph DBMS
	#52	Key-value stores
	#35	Time Series DBMS

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Website

Technical documentation

docs.arcadedb.com

docs.bigobject.io

hbase.apache.org/book.html

nsdb.io/Architecture

Developer

Arcade Data

BigObject, Inc.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Initial release

2021

2015

2008

2017

Current release

September 2021

2.3.4, January 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community edition available

Open Source

Apache version 2

Open Source

Apache Version 2.0

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

Java, Scala

Server operating systems

All OS with a Java VM

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
Unix
Windows

using Cygwin

Linux
macOS

Data scheme

schema-free

yes

schema-free, schema definition possible

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language, no joins

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

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

fluentd
ODBC
RESTful HTTP API

Java API
RESTful HTTP API
Thrift

gRPC
HTTP REST
WebSocket

Supported programming languages

Java

C
C#
C++
Groovy
Java
PHP
Python
Scala

Java
Scala

Server-side scripts

Stored procedures

Lua

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency or Eventual Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

automatically between fact table and dimension tables

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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 (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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More resources

DB-Engines blog posts

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11 August 2021, Krishna Maheshwari (sponsor)

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13 May 2013, Paul Andlinger

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