DBMS > GigaSpaces vs. Graph Engine vs. Hawkular Metrics vs. Prometheus vs. Snowflake

System Properties Comparison GigaSpaces vs. Graph Engine vs. Hawkular Metrics vs. Prometheus vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

Open-source Time Series DBMS and monitoring system

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Graph DBMS
Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

Technical documentation

docs.gigaspaces.com/latest/landing.html

www.graphengine.io/docs/manual

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

prometheus.io/docs

docs.snowflake.net/manuals/index.html

Developer

Gigaspaces Technologies

Microsoft

Community supported by Red Hat

Snowflake Computing Inc.

Initial release

2000

2010

2014

2015

2014

Current release

15.5, September 2020

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

MIT License

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, C++, .Net

.NET and C

Java

Server operating systems

Linux
macOS
Solaris
Windows

.NET

Linux
OS X
Windows

Linux
Windows

hosted

Data scheme

schema-free

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

Numeric data only

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.

XML can be used for describing objects metadata

Import of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

RESTful HTTP API

HTTP REST

RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

Supported programming languages

.Net
C++
Java
Python
Scala

C#
C++
F#
Visual Basic

Go
Java
Python
Ruby

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes, event driven architecture

yes

via Hawkular Alerting

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

based on Cassandra

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

selectable replication factor

based on Cassandra

yes

by Federation

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

none

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Role-based access control

Users with fine-grained authorization concept, user roles and pluggable authentication

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