DBMS > Derby vs. Hawkular Metrics vs. SAP HANA vs. SurrealDB

System Properties Comparison Derby vs. Hawkular Metrics vs. SAP HANA vs. SurrealDB

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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.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

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

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Document store
Graph DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.86
Rank	#203	Overall
	#34	Document stores
	#18	Graph DBMS

Website

db.apache.org/derby

www.hawkular.org

www.sap.com/products/hana.html

surrealdb.com

Technical documentation

db.apache.org/derby/manuals/index.html

www.hawkular.org/hawkular-metrics/docs/user-guide

help.sap.com/hana

surrealdb.com/docs

Developer

Apache Software Foundation

Community supported by Red Hat

SAP

SurrealDB Ltd

Initial release

1997

2014

2010

2022

Current release

10.17.1.0, November 2023

2.0 SPS07 (April 4, 2023), April 2023

v1.5.0, May 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache 2.0

commercial

Open Source

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

Rust

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

Appliance or cloud-service

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

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

SQL-like query language

APIs and other access methods

JDBC

HTTP REST

JDBC
ODBC

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

Java

Go
Java
Python
Ruby

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

Java Stored Procedures

SQLScript, R

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

fine grained access rights according to SQL-standard

yes

yes, based on authentication and database rules

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