DBMS > Geode vs. Google Cloud Spanner vs. Rockset vs. searchxml vs. Snowflake

System Properties Comparison Geode vs. Google Cloud Spanner vs. Rockset vs. searchxml vs. Snowflake

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.

A scalable, reliable search and analytics service in the cloud, built on RocksDB

DBMS for structured and unstructured content wrapped with an application server

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

Primary database model

Key-value store

Relational DBMS

Document store

Native XML DBMS
Search engine

Relational DBMS

Secondary database models

Relational DBMS
Search engine

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

geode.apache.org

cloud.google.com/spanner

rockset.com

www.searchxml.net/category/products

www.snowflake.com

Technical documentation

geode.apache.org/docs

cloud.google.com/spanner/docs

docs.rockset.com

www.searchxml.net/support/handouts

docs.snowflake.net/manuals/index.html

Developer

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

Google

Rockset

informationpartners gmbh

Snowflake Computing Inc.

Initial release

2002

2017

2019

2015

2014

Current release

1.1, February 2017

1.0

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++

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

hosted

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

dynamic typing

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.

ingestion from XML files supported

yes

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language (OQL)

yes

Query statements complying to ANSI 2011

Read-only SQL queries, including JOINs

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

HTTP REST

RESTful HTTP API
WebDAV
XQuery
XSLT

CLI Client
JDBC
ODBC

Supported programming languages

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

Go
Java
JavaScript (Node.js)
Python

C++

most other programming languages supported via APIs

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

on the application server

user defined functions

Triggers

yes

Cache Event Listeners

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication with 3 replicas for regional instances.

yes

sychronisation to multiple collections

yes

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

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

multiple readers, single writer

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)

Access rights for users and organizations can be defined via Rockset console

Domain, group and role-based access control at the document level and for application services

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

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