DBMS > H2 vs. ReductStore vs. RocksDB vs. SAP HANA

System Properties Comparison H2 vs. ReductStore vs. RocksDB 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.

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Primary database model

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	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

www.h2database.com

github.com/reductstore
www.reduct.store

rocksdb.org

www.sap.com/products/hana.html

Technical documentation

www.h2database.com/html/main.html

www.reduct.store/docs

github.com/facebook/rocksdb/wiki

help.sap.com/hana

Developer

Thomas Mueller

ReductStore LLC

Facebook, Inc.

SAP

Initial release

2005

2023

2013

2010

Current release

2.2.220, July 2023

1.9, March 2024

9.2.1, May 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Business Source License 1.1

Open Source

BSD

commercial

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

Java

C++, Rust

C++

Server operating systems

All OS with a Java VM

Docker
Linux
macOS
Windows

Linux

Appliance or cloud-service

Data scheme

yes

schema-free

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

JDBC
ODBC

HTTP API

C++ API
Java API

JDBC
ODBC

Supported programming languages

Java

C++
JavaScript (Node.js)
Python
Rust

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

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

yes

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

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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