DBMS > Apache IoTDB vs. GBase vs. Hazelcast vs. InfinityDB

System Properties Comparison Apache IoTDB vs. GBase vs. Hazelcast vs. InfinityDB

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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

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

A widely adopted in-memory data grid

A Java embedded Key-Value Store which extends the Java Map interface

Primary database model

Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Website

Technical documentation

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

hazelcast.org/imdg/docs

boilerbay.com/infinitydb/manual

Developer

Apache Software Foundation

General Data Technology Co., Ltd.

Hazelcast

Boiler Bay Inc.

Initial release

2018

2004

2008

2002

Current release

1.1.0, April 2023

GBase 8a, GBase 8s, GBase 8c

5.3.6, November 2023

4.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2; commercial licenses available

commercial

Cloud-based only

Only available as a cloud service

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

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

All OS with a Java VM

Data scheme

yes

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

the object must implement a serialization strategy

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

SQL-like query language

Standard with numerous extensions

SQL-like query language

APIs and other access methods

JDBC
Native API

ADO.NET
C API
JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Java

Server-side scripts

Stored procedures

yes

user defined functions

yes

Event Listeners, Executor Services

Triggers

yes

Events

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

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

Replicated Map

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

yes

Role-based access control

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