DBMS > AnzoGraph DB vs. Memcached vs. Oracle vs. RavenDB

System Properties Comparison AnzoGraph DB vs. Memcached vs. Oracle vs. RavenDB

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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

In-memory key-value store, originally intended for caching

Widely used RDBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Secondary database models

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

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Website

cambridgesemantics.com/anzograph

www.memcached.org

www.oracle.com/database

ravendb.net

Technical documentation

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

github.com/memcached/memcached/wiki

docs.oracle.com/en/database

ravendb.net/docs

Developer

Cambridge Semantics

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Oracle

Hibernating Rhinos

Initial release

2018

2003

1980

2010

Current release

2.3, January 2021

1.6.25, March 2024

23c, September 2023

5.4, July 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

BSD license

commercial

restricted free version is available

Open Source

AGPL version 3, commercial license available

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

C and C++

Server operating systems

Linux

FreeBSD
Linux
OS X
Unix
Windows

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

Linux
macOS
Raspberry Pi
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

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

yes

with proprietary extensions

SQL-like query language (RQL)

APIs and other access methods

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

Proprietary protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

C++
Java
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

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

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

Repcached, a Memcached patch, provides this functionallity

Multi-source replication
Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID, Cluster-wide transaction available

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

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

User concepts

Access control

Access rights for users and roles

yes

using SASL (Simple Authentication and Security Layer) protocol

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

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