DBMS > AnzoGraph DB vs. Elasticsearch vs. Google Cloud Firestore vs. Graphite vs. Oracle

System Properties Comparison AnzoGraph DB vs. Elasticsearch vs. Google Cloud Firestore vs. Graphite vs. Oracle

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Widely used RDBMS

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.elastic.co/elasticsearch

firebase.google.com/products/firestore

github.com/graphite-project/graphite-web

www.oracle.com/database

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

firebase.google.com/docs/firestore

graphite.readthedocs.io

docs.oracle.com/en/database

Developer

Cambridge Semantics

Elastic

Google

Chris Davis

Oracle

Initial release

2018

2010

2017

2006

1980

Current release

2.3, January 2021

8.6, January 2023

23c, September 2023

License

Commercial or Open Source

commercial

free trial version available

Open Source

Elastic License

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

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

Python

C and C++

Server operating systems

Linux

All OS with a Java VM

hosted

Linux
Unix

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes

Numeric data only

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 search fields are automatically indexed

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

Java API
RESTful HTTP/JSON API

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

HTTP API
Sockets

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C++
Java
Python

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

JavaScript (Node.js)
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

yes, Firebase Rules & Cloud Functions

PL/SQL

also stored procedures in Java possible

Triggers

yes

by using the 'percolation' feature

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

Multi-source replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

ES-Hadoop Connector

Using Cloud Dataflow

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

yes

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

locking

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

Memcached and Redis integration

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Access rights for users and roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

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