DBMS > AnzoGraph DB vs. Kinetica vs. LeanXcale vs. Snowflake vs. Tibero

System Properties Comparison AnzoGraph DB vs. Kinetica vs. LeanXcale vs. Snowflake vs. Tibero

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

Fully vectorized database across both GPUs and CPUs

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Graph DBMS
RDF store

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.kinetica.com

www.leanxcale.com

www.snowflake.com

us.tmaxsoft.com/products/tibero

Technical documentation

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

docs.kinetica.com

docs.snowflake.net/manuals/index.html

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Cambridge Semantics

Kinetica

LeanXcale

Snowflake Computing Inc.

TmaxSoft

Initial release

2018

2012

2015

2014

2003

Current release

2.3, January 2021

7.1, August 2021

6, April 2015

License

Commercial or Open Source

commercial

free trial version available

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++

C and Assembler

Server operating systems

Linux

hosted

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

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

yes

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.

SQL-like DML and DDL statements

yes

through Apache Derby

yes

APIs and other access methods

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

JDBC
ODBC
RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

CLI Client
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

C++
Java
Python

C++
Java
JavaScript (Node.js)
Python

C
Java
Scala

JavaScript (Node.js)
Python

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

Persistent Stored Procedure (PSM)

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

yes

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency or Eventual Consistency depending on configuration

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

GPU vRAM or System RAM

yes

planned for next version

User concepts

Access control

Access rights for users and roles

Access rights for users and roles on table level

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

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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