DBMS > Apache Impala vs. Interbase vs. Postgres-XL vs. SpaceTime

System Properties Comparison Apache Impala vs. Interbase vs. Postgres-XL vs. SpaceTime

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Light-weight proven RDBMS

originally from Borland

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

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Relational DBMS

Spatial DBMS

Secondary database models

Document store

Document store
Spatial DBMS

Relational DBMS

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	3.78
Rank	#77	Overall
	#41	Relational DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Website

impala.apache.org

www.embarcadero.com/products/interbase

www.postgres-xl.org

www.mireo.com/spacetime

Technical documentation

impala.apache.org/impala-docs.html

docs.embarcadero.com/products/interbase

www.postgres-xl.org/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Embarcadero

Mireo

Initial release

2013

1984

2014

since 2012, originally named StormDB

2020

Current release

4.1.0, June 2022

InterBase 2020, December 2019

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Mozilla public license

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux

Android
iOS
Linux
OS X
Windows

Linux
macOS

Linux

Data scheme

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.

export as XML data possible

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

distributed, parallel query execution

A subset of ANSI SQL is implemented

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

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

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

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

C#
C++
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Interbase procedure and trigger language

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Interbase Change Views

Real-time block device replication (DRBD)

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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 for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

yes

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