DBMS > Hawkular Metrics vs. HyperSQL vs. LeanXcale vs. LevelDB vs. SAP Advantage Database Server

System Properties Comparison Hawkular Metrics vs. HyperSQL vs. LeanXcale vs. LevelDB vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Time Series DBMS

Relational DBMS

Key-value store
Relational DBMS

Key-value store

Relational DBMS

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Website

www.hawkular.org

hsqldb.org

www.leanxcale.com

github.com/google/leveldb

www.sap.com/products/advantage-database-server.html

Technical documentation

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

hsqldb.org/web/hsqlDocsFrame.html

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

Developer

Community supported by Red Hat

LeanXcale

Google

Sybase, SAP

Initial release

2014

2001

2015

2011

1993

Current release

2.7.2, June 2023

1.23, February 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

based on BSD license

commercial

Open Source

BSD

commercial

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

Java

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Illumos
Linux
OS X
Windows

Linux
Windows

Data scheme

schema-free

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

through Apache Derby

yes

APIs and other access methods

HTTP REST

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Go
Java
Python
Ruby

All languages supporting JDBC/ODBC
Java

C
Java
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Delphi
Perl
PHP

Server-side scripts

Stored procedures

Java, SQL

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

with automatic compression on writes

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

caching of (temporary) tables can be configured

User concepts

Access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
5 June 2019, DevClass

provided by Google News

HyperSQL DataBase flaw leaves library vulnerable to RCE
24 October 2022, The Daily Swig

Introduction to JDBC with HSQLDB tutorial
14 November 2022, TheServerSide.com

provided by Google News

Combining operational and analytical databases in a single platform
26 May 2017, Cordis News

provided by Google News

LevelDB in Ruby — SitePoint
22 October 2014, SitePoint

Microsoft Teams stores auth tokens as cleartext in Windows, Linux, Macs
14 September 2022, BleepingComputer

Pliops unveils XDP-Rocks for RocksDB – Blocks and Files
19 October 2022, Blocks & Files

XanMod, Liquorix Kernels Offer Some Advantages On AMD Ryzen 5 Notebook
26 July 2021, Phoronix

Rust-Based Info Stealers Abuse GitHub Codespaces
19 May 2023, Trend Micro

provided by Google News

SAP Announces Q3 2023 Results: Asia Pacific and Japan View
19 October 2023, SAP News

AIRWORLD PART 15: WORLD'S SECOND BEST AIRPORT TERMINAL
30 September 2005, Ad Age

provided by Google News

Share this page