DBMS > Apache Impala vs. Google Cloud Bigtable vs. JaguarDB vs. MaxDB vs. Oracle NoSQL

System Properties Comparison Apache Impala vs. Google Cloud Bigtable vs. JaguarDB vs. MaxDB vs. Oracle NoSQL

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Performant, highly scalable DBMS for AI and IoT applications

A robust and reliable RDBMS optimized to run all major SAP solutions

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Relational DBMS

Key-value store
Wide column store

Key-value store
Vector DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Website

impala.apache.org

cloud.google.com/bigtable

www.jaguardb.com

maxdb.sap.com

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

impala.apache.org/impala-docs.html

cloud.google.com/bigtable/docs

www.jaguardb.com/support.html

maxdb.sap.com/documentation

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Google

DataJaguar, Inc.

SAP, acquired from Software AG (Adabas-D) in 1997

Oracle

Initial release

2013

2015

1984

2011

Current release

4.1.0, June 2022

3.3 July 2023

7.9.10.12, February 2024

24.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

GPL V3.0

commercial

Limited community edition free

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

the server part. Clients available in other languages

C++

Java

Server operating systems

Linux

hosted

Linux

AIX
HP-UX
Linux
Solaris
Windows

Linux
Solaris SPARC/x86

Data scheme

yes

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JDBC
ODBC

ADO.NET
JDBC
ODBC
WebDAV

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Go
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C#
Java
Perl
PHP
Python

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Internal replication in Colossus, and regional replication between two clusters in different zones

Multi-source replication

Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

configurable

ACID within a storage node (=shard)

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

off heap cache

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 (IAM)

rights management via user accounts

fine grained access rights according to SQL-standard

Access rights for users and roles

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More resources

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