DBMS > Apache Kylin vs. Postgres-XL vs. Tarantool vs. Tibero

System Properties Comparison Apache Kylin vs. Postgres-XL vs. Tarantool vs. Tibero

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

kylin.apache.org

www.postgres-xl.org

www.tarantool.io

us.tmaxsoft.com/products/tibero

Technical documentation

kylin.apache.org/docs

www.postgres-xl.org/documentation

www.tarantool.io/en/doc

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Apache Software Foundation, originally contributed from eBay Inc

TmaxSoft

Initial release

2015

2014

since 2012, originally named StormDB

2008

2003

Current release

3.1.0, July 2020

10 R1, October 2018

2.10.0, May 2022

6, April 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Mozilla public license

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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 and C++

C and Assembler

Server operating systems

Linux

Linux
macOS

BSD
Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

yes

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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

XML type, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

distributed, parallel query execution

Full-featured ANSI SQL support

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Open binary protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

Lua, C and SQL stored procedures

Persistent Stored Procedure (PSM)

Triggers

yes

yes, before/after data modification events, on replication events, client session events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

yes, write ahead logging

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, full featured in-memory storage engine with persistence

planned for next version

User concepts

Access control

fine grained access rights according to SQL-standard

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

show all

Recent citations in the news

Migrating from ClickHouse to Apache Doris: Boosting OLAP Performance
9 October 2023, hackernoon.com

Introducing Kyligence Copilot: The AI Copilot for Data to Excel Your KPIs
23 August 2023, insideBIGDATA

Overhauling Apache Kylin for the cloud
18 November 2021, InfoWorld

Top Open-Source Solutions for Business Analytics
24 March 2024, Analytics Insight

eBay's Kylin Becomes a Top-Level Apache Open Source Project
9 December 2015, eBay Inc.

provided by Google News

In-Memory Showdown: Redis vs. Tarantool
4 April 2023, Хабр

TaranHouse: New Big Data Warehouse Announced by Tarantool
4 April 2018, Newswire

Deploying Tarantool Cartridge applications with zero effort (Part 1)
16 December 2019, Хабр

Deploying Tarantool Cartridge applications with zero effort (Part 2)
13 April 2020, Хабр

Тarantool Cartridge: Sharding Lua Backend in Three Lines
9 October 2019, Хабр

provided by Google News

ArkData to Officially Support Domestic Database 'Tibero 7'
23 April 2024, BusinessKorea

How to Succeed at Large-Scale Mainframe Replatforming with TmaxSoft OpenFrame on AWS | Amazon Web Services
2 August 2022, AWS Blog

ArkData's 'Ark for CDC' supports real-time data extraction and replication for Tibero DBMS.
18 April 2023, BusinessKorea

Tmax deploys advanced database management system at UITM's disaster recovery site
30 December 2022, The Malaysian Reserve

Open-source DBMS becoming battleground of public cloud
17 May 2022, Etnews

provided by Google News

Share this page