DBMS > DuckDB vs. Hazelcast vs. Oracle vs. SAP HANA vs. TimescaleDB

System Properties Comparison DuckDB vs. Hazelcast vs. Oracle vs. SAP HANA vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

An embeddable, in-process, column-oriented SQL OLAP RDBMS

A widely adopted in-memory data grid

Widely used RDBMS

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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

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

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Relational DBMS

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

Score	4.57
Rank	#74	Overall
	#40	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

duckdb.org

hazelcast.com

www.oracle.com/database

www.sap.com/products/hana.html

www.timescale.com

Technical documentation

duckdb.org/docs

hazelcast.org/imdg/docs

docs.oracle.com/en/database

help.sap.com/hana

docs.timescale.com

Developer

Hazelcast

Oracle

SAP

Timescale

Initial release

2018

2008

1980

2010

2017

Current release

0.10, February 2024

5.3.6, November 2023

23c, September 2023

2.0 SPS07 (April 4, 2023), April 2023

2.13.0, November 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache Version 2; commercial licenses available

commercial

restricted free version is available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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++

Java

C and C++

Server operating systems

server-less

All OS with a Java VM

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

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

with proprietary extensions

yes

full PostgreSQL SQL syntax

APIs and other access methods

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

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

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

PL/SQL

also stored procedures in Java possible

SQLScript, R

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding, horizontal partitioning

yes

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Replicated Map

Multi-source replication
Source-replica replication

yes

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

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