DBMS > Apache Druid vs. GBase vs. Hypertable vs. Immudb

System Properties Comparison Apache Druid vs. GBase vs. Hypertable vs. Immudb

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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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Wide column store

Key-value store

Secondary database models

Relational DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.31
Rank	#295	Overall
	#42	Key-value stores

Website

druid.apache.org

www.gbase.cn

github.com/codenotary/immudb
immudb.io

Technical documentation

druid.apache.org/docs/latest/design

docs.immudb.io

Developer

Apache Software Foundation and contributors

General Data Technology Co., Ltd.

Hypertable Inc.

Codenotary

Initial release

2012

2004

2009

2020

Current release

29.0.1, April 2024

GBase 8a, GBase 8s, GBase 8c

0.9.8.11, March 2016

1.2.3, April 2022

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

GNU version 3. Commercial license available

Open Source

Apache Version 2.0

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

C++

Server operating systems

Linux
OS X
Unix

Linux

Linux
OS X
Windows

an inofficial Windows port is available

BSD
Linux
macOS
Solaris
Windows
z/OS

Data scheme

yes

schema-less columns are supported

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

yes

SQL

Support of SQL

SQL for querying

Standard with numerous extensions

SQL-like syntax

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
C API
JDBC
ODBC

C++ API
Thrift

gRPC protocol
PostgreSQL wire protocol

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C++
Java
Perl
PHP
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

selectable replication factor on file system level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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.

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

yes

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