DBMS > HEAVY.AI vs. LevelDB vs. Microsoft Access vs. Oracle vs. SWC-DB

System Properties Comparison HEAVY.AI vs. LevelDB vs. Microsoft Access vs. Oracle vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Widely used RDBMS

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Spatial DBMS

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

Time Series DBMS

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

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

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

github.com/google/leveldb

www.microsoft.com/en-us/microsoft-365/access

www.oracle.com/database

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.heavy.ai

github.com/google/leveldb/blob/main/doc/index.md

developer.microsoft.com/en-us/access

docs.oracle.com/en/database

Developer

HEAVY.AI, Inc.

Google

Microsoft

Oracle

Alex Kashirin

Initial release

2016

2011

1992

1980

2020

Current release

5.10, January 2022

1.23, February 2021

1902 (16.0.11328.20222), March 2019

23c, September 2023

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

BSD

commercial

Bundled with Microsoft Office

commercial

restricted free version is available

Open Source

GPL V3

Cloud-based only

Only available as a cloud 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++

C and C++

C++

Server operating systems

Linux

Illumos
Linux
OS X
Windows

Windows

Not a real database server, but making use of DLLs

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

Linux

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC
ODBC
Thrift
Vega

ADO.NET
DAO
ODBC
OLE DB

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Proprietary protocol
Thrift

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

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++

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

PL/SQL

also stored procedures in Java possible

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

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

but no files for transaction logging

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

but no files for transaction logging

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'

User concepts

Access control

fine grained access rights according to SQL-standard

a simple user-level security was built in till version Access 2003

fine grained access rights according to SQL-standard

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