DBMS > Amazon Aurora vs. Apache Impala vs. Interbase vs. SAP HANA vs. Splice Machine

System Properties Comparison Amazon Aurora vs. Apache Impala vs. Interbase vs. SAP HANA vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Analytic DBMS for Hadoop

Light-weight proven RDBMS

originally from Borland

In-memory, column based data store. Available as appliance or cloud service

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

aws.amazon.com/rds/aurora

impala.apache.org

www.embarcadero.com/products/interbase

www.sap.com/products/hana.html

splicemachine.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

impala.apache.org/impala-docs.html

docs.embarcadero.com/products/interbase

help.sap.com/hana

splicemachine.com/how-it-works

Developer

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Embarcadero

SAP

Splice Machine

Initial release

2015

2013

1984

2010

2014

Current release

4.1.0, June 2022

InterBase 2020, December 2019

2.0 SPS07 (April 4, 2023), April 2023

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

Server operating systems

hosted

Linux

Android
iOS
Linux
OS X
Windows

Appliance or cloud-service

Linux
OS X
Solaris
Windows

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.

yes

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC

ADO.NET
JDBC
ODBC

JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

All languages supporting JDBC/ODBC

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Interbase procedure and trigger language

SQLScript, R

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

Interbase Change Views

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Yes, via Full Spark Integration

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

yes, multi-version concurrency control (MVCC)

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, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

yes

Access rights for users, groups and roles according to SQL-standard

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