DBMS > Altibase vs. ClickHouse vs. Faircom EDGE vs. Hazelcast vs. Vertica

System Properties Comparison Altibase vs. ClickHouse vs. Faircom EDGE vs. Hazelcast vs. Vertica

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

A widely adopted in-memory data grid

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Key-value store

Relational DBMS

Column oriented

Secondary database models

Time Series DBMS

Document store

JSON support with IMDG 3.12

Spatial DBMS
Time Series DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

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

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

altibase.com

clickhouse.com

www.faircom.com/products/faircom-edge

hazelcast.com

www.vertica.com

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

clickhouse.com/docs

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

hazelcast.org/imdg/docs

vertica.com/documentation

Developer

Altibase

Clickhouse Inc.

FairCom Corporation

Hazelcast

OpenText

previously Micro Focus and Hewlett Packard

Initial release

1999

2016

1979

2008

2005

Current release

v7.3, 2023, August 2023

v24.4.1.2088-stable, May 2024

V3, October 2020

5.3.6, November 2023

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache 2.0

commercial

Restricted, free version available

Open Source

Apache Version 2; commercial licenses available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

C++

ANSI C, C++

Java

C++

Server operating systems

AIX
HP-UX
Linux

FreeBSD
Linux
macOS

Android
Linux

ARM, x86
Raspbian
Windows

All OS with a Java VM

Linux

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

the object must implement a serialization strategy

Secondary indexes

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

ANSI SQL-92

Close to ANSI SQL (SQL/JSON + extensions)

yes

ANSI SQL queries

SQL-like query language

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JDBC
ODBC
Proprietary protocol

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

C
C++
Java

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

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

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

.Net, JavaScript, C/C++

yes

Event Listeners, Executor Services

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

Events

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

key based and custom

File partitioning

Customizable business rules for partitioning

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

Replicated Map

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

ACID

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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

fine grained access rights according to SQL-standard

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Role-based access control

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Licensing and pricing models

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