DBMS > EXASOL vs. Google Cloud Bigtable vs. HEAVY.AI vs. RDFox vs. SAP HANA

System Properties Comparison EXASOL vs. Google Cloud Bigtable vs. HEAVY.AI vs. RDFox vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

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

High performance knowledge graph and semantic reasoning engine

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

Primary database model

Relational DBMS

Key-value store
Wide column store

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Spatial DBMS

Relational 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	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.exasol.com

cloud.google.com/bigtable

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

www.oxfordsemantic.tech

www.sap.com/products/hana.html

Technical documentation

www.exasol.com/resources

cloud.google.com/bigtable/docs

docs.heavy.ai

docs.oxfordsemantic.tech

help.sap.com/hana

Developer

Exasol

Google

HEAVY.AI, Inc.

Oxford Semantic Technologies

SAP

Initial release

2000

2015

2016

2017

2010

Current release

5.10, January 2022

6.0, Septermber 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 CUDA

C++

Server operating systems

hosted

Linux

Linux
macOS
Windows

Appliance or cloud-service

Data scheme

yes

schema-free

yes

RDF schemas

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

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

JDBC
ODBC
Thrift
Vega

RESTful HTTP API
SPARQL 1.1

JDBC
ODBC

Supported programming languages

Java
Lua
Python
R

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

All languages supporting JDBC/ODBC/Thrift
Python

C
Java

Server-side scripts

Stored procedures

user defined functions

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

yes

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

replication via a shared file system

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

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

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

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

fine grained access rights according to SQL-standard

Roles, resources, and access types

yes

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