DBMS > 4D vs. eXtremeDB vs. Google Cloud Datastore vs. HEAVY.AI vs. SAP HANA

System Properties Comparison 4D vs. eXtremeDB vs. Google Cloud Datastore vs. HEAVY.AI vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.4d.com

www.mcobject.com

cloud.google.com/datastore

github.com/heavyai/heavydb
www.heavy.ai

www.sap.com/products/hana.html

Technical documentation

developer.4d.com

www.mcobject.com/docs/extremedb.htm

cloud.google.com/datastore/docs

docs.heavy.ai

help.sap.com/hana

Developer

4D, Inc

McObject

Google

HEAVY.AI, Inc.

SAP

Initial release

1984

2001

2008

2016

2010

Current release

v20, April 2023

8.2, 2021

5.10, January 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition 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

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

Implementation language

C and C++

C++ and CUDA

Server operating systems

OS X
Windows

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

Linux

Appliance or cloud-service

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

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

close to SQL 92

yes

with the option: eXtremeSQL

SQL-like query language (GQL)

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

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

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

JDBC
ODBC

Supported programming languages

4D proprietary IDE
PHP

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

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

Server-side scripts

Stored procedures

yes

using Google App Engine

SQLScript, R

Triggers

yes

by defining events

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning / sharding

Sharding

Round robin

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source 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

Multi-source replication using Paxos

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

Users and groups

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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,...
» more

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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