DBMS > Hyprcubd vs. Ingres vs. JanusGraph vs. LeanXcale vs. Lovefield

System Properties Comparison Hyprcubd vs. Ingres vs. JanusGraph vs. LeanXcale vs. Lovefield

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Serverless Time Series DBMS

Well established RDBMS

A Graph DBMS optimized for distributed clusters

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Time Series DBMS

Relational DBMS

Graph DBMS

Key-value store
Relational DBMS

Relational DBMS

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

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

hyprcubd.com (offline)

www.actian.com/databases/ingres

janusgraph.org

www.leanxcale.com

google.github.io/lovefield

Technical documentation

docs.actian.com/ingres

docs.janusgraph.org

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Hyprcubd, Inc.

Actian Corporation

Linux Foundation; originally developed as Titan by Aurelius

LeanXcale

Google

Initial release

1974

originally developed at University Berkely in early 1970s

2017

2015

2014

Current release

11.2, May 2022

0.6.3, February 2023

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

JavaScript

Server operating systems

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
OS X
Unix
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

through Apache Derby

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

gRPC (https)

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

Clojure
Java
Python

C
Java
Scala

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Ingres Star to access multiple databases simultaneously

yes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Ingres Replicator

yes

none

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

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

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

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

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

token access

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

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