DBMS > Geode vs. H2GIS vs. Microsoft Azure Cosmos DB vs. Solr vs. TinkerGraph

System Properties Comparison Geode vs. H2GIS vs. Microsoft Azure Cosmos DB vs. Solr vs. TinkerGraph

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

Spatial extension of H2

Globally distributed, horizontally scalable, multi-model database service

A widely used distributed, scalable search engine based on Apache Lucene

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Key-value store

Spatial DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Search engine

Graph DBMS

Secondary database models

Relational DBMS

Spatial DBMS

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

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

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

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

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

geode.apache.org

www.h2gis.org

azure.microsoft.com/services/cosmos-db

solr.apache.org

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

geode.apache.org/docs

www.h2gis.org/docs/home

learn.microsoft.com/azure/cosmos-db

solr.apache.org/resources.html

Developer

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

CNRS

Microsoft

Apache Software Foundation

Initial release

2002

2013

2014

2006

2009

Current release

1.1, February 2017

9.6.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

LGPL 3.0

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

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

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

hosted

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

schema-free

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

supports customizable data types and automatic 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.

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL-like query language (OQL)

yes

SQL-like query language

Solr Parallel SQL Interface

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

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

Java API
RESTful HTTP/JSON API

TinkerPop 3

Supported programming languages

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

Java

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

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Groovy
Java

Server-side scripts

Stored procedures

user defined functions

yes

based on H2

JavaScript

Java plugins

Triggers

yes

Cache Event Listeners

yes

JavaScript

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

based on H2

yes

Implicit feature of the cloud service

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

yes, on a single node

ACID

Multi-item ACID transactions with snapshot isolation within a partition

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

optional

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

yes

based on H2

Access rights can be defined down to the item level

yes

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