DBMS > Apache IoTDB vs. Google BigQuery vs. H2GIS vs. Interbase vs. Microsoft Access

System Properties Comparison Apache IoTDB vs. Google BigQuery vs. H2GIS vs. Interbase vs. Microsoft Access

Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Large scale data warehouse service with append-only tables

Spatial extension of H2

Light-weight proven RDBMS

originally from Borland

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Primary database model

Secondary database models

Relational DBMS

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

Score	1.19
Rank	#176	Overall
	#15	Time Series DBMS

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	0.05
Rank	#372	Overall
	#7	Spatial DBMS

Score	5.04
Rank	#71	Overall
	#39	Relational DBMS

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

Website

iotdb.apache.org

cloud.google.com/bigquery

www.h2gis.org

www.embarcadero.com/products/interbase

www.microsoft.com/en-us/microsoft-365/access

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

cloud.google.com/bigquery/docs

www.h2gis.org/docs/home

docs.embarcadero.com/products/interbase

developer.microsoft.com/en-us/access

Developer

Apache Software Foundation

Google

CNRS

Embarcadero

Microsoft

Initial release

2018

2010

2013

1984

1992

Current release

1.1.0, April 2023

InterBase 2020, December 2019

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

LGPL 3.0

commercial

Bundled with Microsoft Office

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++

Server operating systems

All OS with a Java VM (>= 1.8)

hosted

Android
iOS
Linux
OS X
Windows

Windows

Not a real database server, but making use of DLLs

Data scheme

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.

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

but not compliant to any SQL standard

APIs and other access methods

JDBC
Native API

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

based on H2

yes

Interbase procedure and trigger language

yes

since Access 2010 using the ACE-engine

Triggers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

yes

based on H2

Interbase Change Views

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

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

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Multiversion concurreny control

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

In-memory capabilities

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

yes

User concepts

Access control

yes

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

Google Cloud Identity & Access Management (IAM)

yes

based on H2

fine grained access rights according to SQL-standard

a simple user-level security was built in till version Access 2003

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.