DBMS > Geode vs. Google Cloud Spanner vs. IBM Db2 warehouse vs. Snowflake vs. SQream DB

System Properties Comparison Geode vs. Google Cloud Spanner vs. IBM Db2 warehouse vs. Snowflake vs. SQream DB

Editorial information provided by DB-Engines

Name

Description

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Cloud-based data warehousing service

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

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

Primary database model

Key-value store

Relational DBMS

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

Score	1.99
Rank	#133	Overall
	#23	Key-value stores

Score	2.89
Rank	#105	Overall
	#53	Relational DBMS

Score	1.34
Rank	#166	Overall
	#76	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	0.73
Rank	#228	Overall
	#105	Relational DBMS

Website

geode.apache.org

cloud.google.com/spanner

www.ibm.com/products/db2/warehouse

www.snowflake.com

sqream.com

Technical documentation

geode.apache.org/docs

cloud.google.com/spanner/docs

docs.snowflake.net/manuals/index.html

docs.sqream.com

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Google

IBM

Snowflake Computing Inc.

SQream Technologies

Initial release

2002

2017

2014

2017

Current release

1.1, February 2017

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

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++, CUDA, Haskell, Java, Scala

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

hosted

Linux

Data scheme

schema-free

yes

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

yes

Typing

predefined data types such as float or date

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (OQL)

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

.NET Client API
JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

Go
Java
JavaScript (Node.js)
Python

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

PL/SQL, SQL PL

user defined functions

user defined functions in Python

Triggers

yes

Cache Event Listeners

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication with 3 replicas for regional instances.

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

yes, on a single node

ACID

Strict serializable isolation

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

User concepts

Access control

Access rights per client and object definable

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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

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