DBMS > Apache IoTDB vs. GBase vs. GeoSpock vs. Interbase

System Properties Comparison Apache IoTDB vs. GBase vs. GeoSpock vs. Interbase

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Spatial and temporal data processing engine for extreme data scale

Light-weight proven RDBMS

originally from Borland

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Website

iotdb.apache.org

www.gbase.cn

geospock.com

www.embarcadero.com/products/interbase

Technical documentation

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

docs.embarcadero.com/products/interbase

Developer

Apache Software Foundation

General Data Technology Co., Ltd.

GeoSpock

Embarcadero

Initial release

2018

2004

1984

Current release

1.1.0, April 2023

GBase 8a, GBase 8s, GBase 8c

2.0, September 2019

InterBase 2020, December 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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, Java, Python

Java, Javascript

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

hosted

Android
iOS
Linux
OS X
Windows

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.

yes

export as XML data possible

Secondary indexes

yes

temporal, categorical

yes

SQL

Support of SQL

SQL-like query language

Standard with numerous extensions

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

JDBC
Native API

ADO.NET
C API
JDBC
ODBC

JDBC

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

Server-side scripts

Stored procedures

yes

user defined functions

yes

Interbase procedure and trigger language

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning (by range, list and hash) and vertical partitioning

Automatic sharding

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

Interbase Change Views

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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

yes

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

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