DBMS > BigchainDB vs. Heroic vs. JanusGraph vs. Postgres-XL vs. SAP Advantage Database Server

System Properties Comparison BigchainDB vs. Heroic vs. JanusGraph vs. Postgres-XL vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

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 Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	1.91
Rank	#135	Overall
	#12	Graph DBMS

Score	0.52
Rank	#256	Overall
	#117	Relational DBMS

Website

www.bigchaindb.com

github.com/spotify/heroic

janusgraph.org

www.postgres-xl.org

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

Technical documentation

bigchaindb.readthedocs.io/en/latest

spotify.github.io/heroic

docs.janusgraph.org

www.postgres-xl.org/documentation

Developer

Spotify

Linux Foundation; originally developed as Titan by Aurelius

Sybase, SAP

Initial release

2016

2014

2017

2014

since 2012, originally named StormDB

1993

Current release

0.6.3, February 2023

10 R1, October 2018

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Mozilla public license

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

Server operating systems

Linux

Linux
OS X
Unix
Windows

Linux
macOS

Linux
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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

CLI Client
RESTful HTTP API

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

Clojure
Java
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

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

caching of (temporary) tables can be configured

User concepts

Access control

yes

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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