DBMS > Derby vs. eXtremeDB vs. Google BigQuery vs. SAP HANA

System Properties Comparison Derby vs. eXtremeDB vs. Google BigQuery vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Natively in-memory DBMS with options for persistency, high-availability and clustering

Large scale data warehouse service with append-only tables

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

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

db.apache.org/derby

www.mcobject.com

cloud.google.com/bigquery

www.sap.com/products/hana.html

Technical documentation

db.apache.org/derby/manuals/index.html

www.mcobject.com/docs/extremedb.htm

cloud.google.com/bigquery/docs

help.sap.com/hana

Developer

Apache Software Foundation

McObject

Google

SAP

Initial release

1997

2001

2010

Current release

10.17.1.0, November 2023

8.2, 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache version 2

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

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

Implementation language

Java

C and C++

Server operating systems

All OS with a Java VM

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

Appliance or cloud-service

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

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

yes

APIs and other access methods

JDBC

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

Java

.Net
C
C#
C++
Java
Lua
Python
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

yes

user defined functions

in JavaScript

SQLScript, R

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning / sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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

fine grained access rights according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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