DBMS > Google BigQuery vs. Heroic vs. Hyprcubd vs. Informix vs. TerminusDB

System Properties Comparison Google BigQuery vs. Heroic vs. Hyprcubd vs. Informix vs. TerminusDB

Editorial information provided by DB-Engines

Name

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

Description

Large scale data warehouse service with append-only tables

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

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

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

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Graph DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

Document store
RDF store

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

cloud.google.com/bigquery

github.com/spotify/heroic

hyprcubd.com (offline)

www.ibm.com/products/informix

terminusdb.com

Technical documentation

cloud.google.com/bigquery/docs

spotify.github.io/heroic

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

terminusdb.github.io/terminusdb/#

Developer

Google

Spotify

Hyprcubd, Inc.

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

DataChemist Ltd.

Initial release

2010

2014

1984

2018

Current release

14.10.FC5, November 2020

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free developer edition available

Open Source

GPL V3

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

C, C++ and Java

Prolog, Rust

Server operating systems

hosted

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

Since Version 12.10 support for JSON/BSON datatypes

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

yes

SQL

Support of SQL

yes

SQL-like query language

yes

SQL-like query language (WOQL)

APIs and other access methods

RESTful HTTP/JSON API

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

gRPC (https)

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

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

yes

Multi-source replication
Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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

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

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

Google Cloud Identity & Access Management (IAM)

token access

Users with fine-grained authentication, authorization, and auditing controls

Role-based access control

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