DBMS > Apache Impala vs. Ingres vs. SAP HANA vs. YDB

System Properties Comparison Apache Impala vs. Ingres vs. SAP HANA vs. YDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Well established RDBMS

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

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Document store
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	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.35
Rank	#278	Overall
	#43	Document stores
	#127	Relational DBMS

Website

impala.apache.org

www.actian.com/databases/ingres

www.sap.com/products/hana.html

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

impala.apache.org/impala-docs.html

docs.actian.com/ingres

help.sap.com/hana

ydb.tech/en/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Actian Corporation

SAP

Yandex

Initial release

2013

1974

originally developed at University Berkely in early 1970s

2010

2019

Current release

4.1.0, June 2022

11.2, May 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0; commercial license available

Cloud-based only

Only available as a cloud service

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++

Server operating systems

Linux

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Appliance or cloud-service

Linux

Data scheme

yes

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

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language (YQL)

APIs and other access methods

JDBC
ODBC

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

JDBC
ODBC

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Ingres Replicator

yes

Active-passive shard 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

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

MVCC

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

Access rights defined for Yandex Cloud users

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