DBMS > BigchainDB vs. Heroic vs. IRONdb vs. OrigoDB vs. SAP Advantage Database Server

System Properties Comparison BigchainDB vs. Heroic vs. IRONdb vs. OrigoDB vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

A fully ACID in-memory object graph database

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Document store

Time Series DBMS

Document store
Object oriented DBMS

Relational DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

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

Website

www.bigchaindb.com

github.com/spotify/heroic

www.circonus.com/solutions/time-series-database/

origodb.com

www.sap.com/products/advantage-database-server.html

Technical documentation

bigchaindb.readthedocs.io/en/latest

spotify.github.io/heroic

docs.circonus.com/irondb/category/getting-started

origodb.com/docs

Developer

Spotify

Circonus LLC.

Robert Friberg et al

Sybase, SAP

Initial release

2016

2014

2017

2009

under the name LiveDB

1993

Current release

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache 2.0

commercial

Open Source

commercial

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

Python

Java

C and C++

Server operating systems

Linux

Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

CLI Client
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP API

.NET Client API
HTTP API
LINQ

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

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

.Net

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes, in Lua

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

configurable replication factor, datacenter aware

Source-replica replication

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

depending on model

yes

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,with MongoDB ord RethinkDB

yes

Write ahead log

yes

In-memory capabilities

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

yes

caching of (temporary) tables can be configured

User concepts

Access control

yes

Role based authorization

fine grained access rights according to SQL-standard

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More resources

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