DBMS > GigaSpaces vs. InfluxDB vs. Microsoft Azure Cosmos DB vs. Yaacomo

System Properties Comparison GigaSpaces vs. InfluxDB vs. Microsoft Azure Cosmos DB vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

DBMS for storing time series, events and metrics

Globally distributed, horizontally scalable, multi-model database service

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Graph DBMS
Search engine

Spatial DBMS

with GEO package

Spatial DBMS

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

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

www.gigaspaces.com

www.influxdata.com/products/influxdb-overview

azure.microsoft.com/services/cosmos-db

yaacomo.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

docs.influxdata.com/influxdb

learn.microsoft.com/azure/cosmos-db

Developer

Gigaspaces Technologies

Microsoft

Q2WEB GmbH

Initial release

2000

2013

2014

2009

Current release

15.5, September 2020

2.7.6, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

MIT-License; commercial enterprise version available

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

Server operating systems

Linux
macOS
Solaris
Windows

Linux
OS X

through Homebrew

hosted

Android
Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

JSON types

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

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-99 for query and DML statements

SQL-like query language

yes

APIs and other access methods

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

HTTP API
JSON over UDP

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
ODBC

Supported programming languages

.Net
C++
Java
Python
Scala

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes, event driven architecture

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

Sharding

Implicit feature of the cloud service

horizontal partitioning

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

in enterprise version only

yes

Implicit feature of the cloud service

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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

Depending on used storage engine

yes

User concepts

Access control

Role-based access control

simple rights management via user accounts

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Key customers

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Market metrics

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Licensing and pricing models

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News

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9 May 2024

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7 May 2024

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2 May 2024

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