DBMS > Heroic vs. HugeGraph vs. jBASE vs. Linter vs. Newts

System Properties Comparison Heroic vs. HugeGraph vs. jBASE vs. Linter vs. Newts

Editorial information provided by DB-Engines

Name

Description

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

A fast-speed and highly-scalable Graph DBMS

A robust multi-value DBMS comprising development tools and middleware

RDBMS for high security requirements

Time Series DBMS based on Cassandra

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Website

github.com/spotify/heroic

github.com/hugegraph
hugegraph.apache.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

linter.ru

opennms.github.io/newts

Technical documentation

spotify.github.io/heroic

hugegraph.apache.org/docs

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

github.com/OpenNMS/newts/wiki

Developer

Spotify

Baidu

Rocket Software (formerly Zumasys)

relex.ru

OpenNMS Group

Initial release

2014

2018

1991

1990

2014

Current release

0.9

5.7

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

Open Source

Apache 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

C and C++

Java

Server operating systems

Linux
macOS
Unix

AIX
Linux
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

Secondary indexes

yes

via Elasticsearch

yes

also supports composite index and range index

yes

SQL

Support of SQL

Embedded SQL for jBASE in BASIC

yes

APIs and other access methods

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

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

HTTP REST
Java API

Supported programming languages

Groovy
Java
Python

.Net
Basic
Jabbascript
Java

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Java

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

Source-replica replication

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

edges in graph

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

In-memory capabilities

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

yes

User concepts

Access control

Users, roles and permissions

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

POC exploit code published for 9.8-rated Apache HugeGraph RCE flaw
7 June 2024, The Register

AI, Lockbit, Veeam, Club Penguin, Kali, Commando Cat, HugeGraph, Aaran Leyland… – SWN #391
7 June 2024, SC Media

PoC Exploit Released for High Severity Apache HugeGraph RCE flaw
7 June 2024, CybersecurityNews

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

Top 5 CVEs and Vulnerabilities of May 2024
3 June 2024, Security Boulevard

provided by Google News

Share this page