DBMS > Apache Impala vs. Google Cloud Firestore vs. Oracle vs. SAP HANA vs. SQream DB

System Properties Comparison Apache Impala vs. Google Cloud Firestore vs. Oracle vs. SAP HANA vs. SQream DB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Widely used RDBMS

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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	7.85
Rank	#51	Overall
	#8	Document stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

impala.apache.org

firebase.google.com/products/firestore

www.oracle.com/database

www.sap.com/products/hana.html

sqream.com

Technical documentation

impala.apache.org/impala-docs.html

firebase.google.com/docs/firestore

docs.oracle.com/en/database

help.sap.com/hana

docs.sqream.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Google

Oracle

SAP

SQream Technologies

Initial release

2013

2017

1980

2010

2017

Current release

4.1.0, June 2022

23c, September 2023

2.0 SPS07 (April 4, 2023), April 2023

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

restricted free version is available

commercial

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

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Implementation language

C++

C and C++

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Appliance or cloud-service

Linux

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes, Firebase Rules & Cloud Functions

PL/SQL

also stored procedures in Java possible

SQLScript, R

user defined functions in Python

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

yes

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

Multi-source replication
Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Using Cloud Dataflow

can be realized in PL/SQL

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

yes

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

yes

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