DBMS > ArcadeDB vs. BigchainDB vs. Hawkular Metrics vs. Sphinx

System Properties Comparison ArcadeDB vs. BigchainDB vs. Hawkular Metrics vs. Sphinx

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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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Document store

Time Series DBMS

Search engine

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

Score	0.02
Rank	#374	Overall
	#52	Document stores
	#38	Graph DBMS
	#56	Key-value stores
	#38	Time Series DBMS

Score	0.76
Rank	#216	Overall
	#36	Document stores

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

Technical documentation

docs.arcadedb.com

bigchaindb.readthedocs.io/en/latest

www.hawkular.org/hawkular-metrics/docs/user-guide

sphinxsearch.com/docs

Developer

Arcade Data

Community supported by Red Hat

Sphinx Technologies Inc.

Initial release

2021

2016

2014

2001

Current release

September 2021

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPL v3

Open Source

Apache 2.0

Open Source

GPL version 2, commercial licence available

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

Python

Java

C++

Server operating systems

All OS with a Java VM

Linux

Linux
OS X
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

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

full-text index on all search fields

SQL

Support of SQL

SQL-like query language, no joins

SQL-like query language (SphinxQL)

APIs and other access methods

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

CLI Client
RESTful HTTP API

HTTP REST

Proprietary protocol

Supported programming languages

Java

Go
Haskell
Java
JavaScript
Python
Ruby

Go
Java
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

User concepts

Access control

yes

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More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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