DBMS > Alibaba Cloud Table Store vs. Apache Impala vs. Firebird vs. LeanXcale

System Properties Comparison Alibaba Cloud Table Store vs. Apache Impala vs. Firebird vs. LeanXcale

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Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Analytic DBMS for Hadoop

Firebird is an open source RDBMS forked from Borland's InterBase

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Primary database model

Wide column store

Relational DBMS

Key-value store
Relational DBMS

Secondary database models

Document store

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Website

www.alibabacloud.com/product/table-store

impala.apache.org

www.firebirdsql.org

www.leanxcale.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

impala.apache.org/impala-docs.html

www.firebirdsql.org/en/reference-manuals

Developer

Alibaba

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Firebird Foundation

LeanXcale

Initial release

2016

2013

2000

As fork of Borland's InterBase

2015

Current release

4.1.0, June 2022

5.0.0, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Initial Developer's Public License

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

Server operating systems

hosted

Linux

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Data scheme

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

through Apache Derby

APIs and other access methods

HTTP API

JDBC
ODBC

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

Java
Python

All languages supporting JDBC/ODBC

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C
Java
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

PSQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

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

Access rights based on subaccounts and tokens

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Users with fine-grained authorization concept

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