DBMS > GeoMesa vs. Memcached vs. Pinecone vs. Snowflake vs. SQream DB

System Properties Comparison GeoMesa vs. Memcached vs. Pinecone vs. Snowflake vs. SQream DB

Editorial information provided by DB-Engines

Name

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

In-memory key-value store, originally intended for caching

A managed, cloud-native vector database

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	3.23
Rank	#92	Overall
	#2	Vector DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

github.com/memcached/memcached/wiki

docs.pinecone.io/docs/overview

docs.snowflake.net/manuals/index.html

docs.sqream.com

Developer

CCRi and others

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Pinecone Systems, Inc

Snowflake Computing Inc.

SQream Technologies

Initial release

2014

2003

2019

2014

2017

Current release

5.0.0, May 2024

1.6.27, May 2024

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

BSD license

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

C++, CUDA, Haskell, Java, Scala

Server operating systems

FreeBSD
Linux
OS X
Unix
Windows

hosted

Linux

Data scheme

yes

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

yes

yes, ANSI Standard SQL Types

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Proprietary protocol

RESTful HTTP API

CLI Client
JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

Python

JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

user defined functions in Python

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

none

yes

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

none

Repcached, a Memcached patch, provides this functionallity

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

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

In-memory capabilities

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

depending on storage layer

User concepts

Access control

yes

depending on the DBMS used for storage

yes

using SASL (Simple Authentication and Security Layer) protocol

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

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