DBMS > Hawkular Metrics vs. HugeGraph vs. LokiJS vs. SAP Advantage Database Server

System Properties Comparison Hawkular Metrics vs. HugeGraph vs. LokiJS vs. SAP Advantage Database Server

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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.

A fast-speed and highly-scalable Graph DBMS

In-memory JavaScript DBMS

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

Primary database model

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Website

www.hawkular.org

github.com/hugegraph
hugegraph.apache.org

github.com/techfort/LokiJS

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

Technical documentation

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

hugegraph.apache.org/docs

techfort.github.io/LokiJS

Developer

Community supported by Red Hat

Baidu

Sybase, SAP

Initial release

2014

2018

2014

1993

Current release

0.9

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

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

JavaScript

Server operating systems

Linux
OS X
Windows

Linux
macOS
Unix

server-less, requires a JavaScript environment (browser, Node.js)

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

also supports composite index and range index

yes

via views

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST

Java API
RESTful HTTP API
TinkerPop Gremlin

JavaScript API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Go
Java
Python
Ruby

Groovy
Java
Python

JavaScript

Delphi
Perl
PHP

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

View functions in JavaScript

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

Users, roles and permissions

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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