DBMS > ArcadeDB vs. Graphite vs. InterSystems Caché vs. Postgres-XL

System Properties Comparison ArcadeDB vs. Graphite vs. InterSystems Caché vs. Postgres-XL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

A multi-model DBMS and application server

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Time Series DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	0.02
Rank	#374	Overall
	#52	Document stores
	#38	Graph DBMS
	#56	Key-value stores
	#38	Time Series DBMS

Score	5.19
Rank	#62	Overall
	#4	Time Series DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Website

arcadedb.com

github.com/graphite-project/graphite-web

www.intersystems.com/products/cache

www.postgres-xl.org

Technical documentation

docs.arcadedb.com

graphite.readthedocs.io

docs.intersystems.com

www.postgres-xl.org/documentation

Developer

Arcade Data

Chris Davis

InterSystems

Initial release

2021

2006

1997

2014

since 2012, originally named StormDB

Current release

September 2021

2018.1.4, May 2020

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

Mozilla public license

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

Python

Server operating systems

All OS with a Java VM

Linux
Unix

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux
macOS

Data scheme

schema-free

yes

depending on used data model

yes

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

distributed, parallel query execution

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

HTTP API
Sockets

.NET Client API
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Java

JavaScript (Node.js)
Python

C#
C++
Java

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

locking

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

Access rights for users, groups and roles

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

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

Collecting, storing, and analyzing your DevOps workloads with open-source Telegraf, Amazon Timestream, and Grafana
25 November 2020, AWS Blog

provided by Google News

InterSystems
5 March 2019, International Spectrum Magazine

Announcing IBM Spectrum Sentinel: Building a Cyber Resilient Future
24 June 2022, IBM

Associative Data Modeling Demystified – Part1
9 July 2016, Data Science Central

Choosing a Database Technology. A roadmap and process overview | by Shirish Joshi
23 February 2020, Towards Data Science

New Release of MITS Report Expands Database Support, Improves Usability and Integration Capabilities
13 February 2019, International Spectrum Magazine

provided by Google News

Share this page