DBMS > Galaxybase vs. Google BigQuery vs. Heroic vs. Hypertable vs. IBM Db2

System Properties Comparison Galaxybase vs. Google BigQuery vs. Heroic vs. Hypertable vs. IBM Db2

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Scalable, ACID-compliant native distributed parallel graph platform

Large scale data warehouse service with append-only tables

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

An open source BigTable implementation based on distributed file systems such as Hadoop

Common in IBM host environments, 2 different versions for host and Windows/Linux

Primary database model

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Website

galaxybase.com

cloud.google.com/bigquery

github.com/spotify/heroic

www.ibm.com/products/db2

Technical documentation

cloud.google.com/bigquery/docs

spotify.github.io/heroic

www.ibm.com/docs/en/db2

Developer

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Google

Spotify

Hypertable Inc.

IBM

Initial release

2017

2010

2014

2009

1983

host version

Current release

Nov 20, November 2021

0.9.8.11, March 2016

12.1, October 2016

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GNU version 3. Commercial license available

commercial

free version is available

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

C and Java

Java

C++

C and C++

Server operating systems

Linux

hosted

Linux
OS X
Windows

an inofficial Windows port is available

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Data scheme

Strong typed schema

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

APIs and other access methods

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

RESTful HTTP/JSON API

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

C++ API
Thrift

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

Supported programming languages

Go
Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined procedures and functions

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

only with Windows/Unix/Linux Version

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor on file system level

yes

with separate tools (MQ, InfoSphere)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

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 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

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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