DBMS > Google BigQuery vs. Hyprcubd vs. mSQL vs. OrigoDB vs. Titan

System Properties Comparison Google BigQuery vs. Hyprcubd vs. mSQL vs. OrigoDB vs. Titan

Editorial information provided by DB-Engines

Name

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

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

Large scale data warehouse service with append-only tables

Serverless Time Series DBMS

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Document store
Object oriented DBMS

Graph DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

cloud.google.com/bigquery

hyprcubd.com (offline)

hughestech.com.au/products/msql

origodb.com

github.com/thinkaurelius/titan

Technical documentation

cloud.google.com/bigquery/docs

origodb.com/docs

github.com/thinkaurelius/titan/wiki

Developer

Google

Hyprcubd, Inc.

Hughes Technologies

Robert Friberg et al

Aurelius, owned by DataStax

Initial release

2010

1994

2009

under the name LiveDB

2012

Current release

4.4, October 2021

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

Apache license, version 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

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

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

SQL

Support of SQL

yes

SQL-like query language

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

RESTful HTTP/JSON API

gRPC (https)

JDBC
ODBC

.NET Client API
HTTP API
LINQ

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net

Clojure
Java
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

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

Immediate Consistency

Eventual Consistency

none

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

depending on model

yes

Relationships in graph

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

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

In-memory capabilities

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

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

token access

Role based authorization

User authentification and security via Rexster Graph Server

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