DBMS > Apache IoTDB vs. Cachelot.io vs. GBase vs. Hypertable

System Properties Comparison Apache IoTDB vs. Cachelot.io vs. GBase vs. Hypertable

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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

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

In-memory caching system

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

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

Primary database model

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

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Website

iotdb.apache.org

cachelot.io

www.gbase.cn

Technical documentation

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

Developer

Apache Software Foundation

General Data Technology Co., Ltd.

Hypertable Inc.

Initial release

2018

2015

2004

2009

Current release

1.1.0, April 2023

GBase 8a, GBase 8s, GBase 8c

0.9.8.11, March 2016

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Simplified BSD License

commercial

Open Source

GNU version 3. Commercial license available

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++

C, Java, Python

C++

Server operating systems

All OS with a Java VM (>= 1.8)

FreeBSD
Linux
OS X

Linux

Linux
OS X
Windows

an inofficial Windows port is available

Data scheme

yes

schema-free

yes

schema-free

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

Secondary indexes

yes

restricted

only exact value or prefix value scans

SQL

Support of SQL

SQL-like query language

Standard with numerous extensions

APIs and other access methods

JDBC
Native API

Memcached protocol

ADO.NET
C API
JDBC
ODBC

C++ API
Thrift

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

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

Sharding

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

none

yes

selectable replication factor on file system level

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

none

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

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

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