DBMS > AnzoGraph DB vs. Cubrid vs. Elasticsearch vs. Snowflake

System Properties Comparison AnzoGraph DB vs. Cubrid vs. Elasticsearch vs. Snowflake

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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

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

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

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	0.27
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	134.78
Rank	#7	Overall
	#1	Search engines

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

cambridgesemantics.com/anzograph

cubrid.com (korean)
cubrid.org (english)

www.elastic.co/elasticsearch

www.snowflake.com

Technical documentation

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

cubrid.org/manuals

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

docs.snowflake.net/manuals/index.html

Developer

Cambridge Semantics

CUBRID Corporation, CUBRID Foundation

Elastic

Snowflake Computing Inc.

Initial release

2018

2008

2010

2014

Current release

2.3, January 2021

11.0, January 2021

8.6, January 2023

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

Open Source

Elastic License

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

C, C++, Java

Java

Server operating systems

Linux

Linux
Windows

All OS with a Java VM

hosted

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

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

yes

support of semi-structured data formats (JSON, XML, Avro)

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

All search fields are automatically indexed

SQL

Support of SQL

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

yes

SQL-like query language

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC
OLE DB

Java API
RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

Supported programming languages

C++
Java
Python

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

Java Stored Procedures

yes

user defined functions

Triggers

yes

by using the 'percolation' feature

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Eventual Consistency

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

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

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

Memcached and Redis integration

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

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

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