DBMS > Geode vs. OrigoDB vs. SQLite vs. Sqrrl vs. Stardog

System Properties Comparison Geode vs. OrigoDB vs. SQLite vs. Sqrrl vs. Stardog

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

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

A fully ACID in-memory object graph database

Widely used embeddable, in-process RDBMS

Adaptable, secure NoSQL built on Apache Accumulo

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Key-value store

Document store
Object oriented DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS
RDF store

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

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

sqrrl.com

Technical documentation

geode.apache.org/docs

origodb.com/docs

www.sqlite.org/docs.html

docs.stardog.com

Developer

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

Robert Friberg et al

Dwayne Richard Hipp

Amazon

originally Sqrrl Data, Inc.

Stardog-Union

Initial release

2002

2009

under the name LiveDB

2000

2012

2010

Current release

1.1, February 2017

3.46.0 (23 May 2024), May 2024

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Public Domain

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

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

Linux
Windows

server-less

Linux

Linux
macOS
Windows

Data scheme

schema-free

yes

dynamic column types

schema-free

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

yes

not rigid because of 'dynamic typing' concept.

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.

can be achieved using .NET

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language (OQL)

yes

SQL-92 is not fully supported

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

.NET Client API
HTTP API
LINQ

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

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

.Net

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

Cache Event Listeners

yes

Domain Events

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

none

Sharding

making use of Hadoop

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

none

selectable replication factor

making use of Hadoop

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

depending on model

yes

relationships in graphs

Transaction concepts

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

yes, on a single node

ACID

Atomic updates per row, document, or graph entity

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Role based authorization

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

Access rights for users and roles

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