DBMS > BigObject vs. Heroic vs. SWC-DB vs. TerminusDB

System Properties Comparison BigObject vs. Heroic vs. SWC-DB vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

A high performance, scalable Wide Column DBMS

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Wide column store

Graph DBMS

Secondary database models

Time Series DBMS

Document store
RDF store

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

Score	0.13
Rank	#342	Overall
	#150	Relational DBMS

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	0.01
Rank	#387	Overall
	#13	Wide column stores

Score	0.22
Rank	#323	Overall
	#28	Graph DBMS

Website

bigobject.io

github.com/spotify/heroic

github.com/kashirin-alex/swc-db
www.swcdb.org

terminusdb.com

Technical documentation

docs.bigobject.io

spotify.github.io/heroic

terminusdb.github.io/terminusdb/#

Developer

BigObject, Inc.

Spotify

Alex Kashirin

DataChemist Ltd.

Initial release

2015

2014

2020

2018

Current release

0.5, April 2021

11.0.0, January 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

GPL V3

Open Source

GPL V3

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

C++

Prolog, Rust

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

Data scheme

yes

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

via Elasticsearch

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

SQL-like query language (WOQL)

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

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

Proprietary protocol
Thrift

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C++

JavaScript
Python

Server-side scripts

Stored procedures

Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

in-memory journaling

In-memory capabilities

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

yes

User concepts

Access control

Role-based access control

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