DBMS > atoti vs. Kinetica vs. Snowflake vs. Spark SQL vs. TerminusDB

System Properties Comparison atoti vs. Kinetica vs. Snowflake vs. Spark SQL vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Fully vectorized database across both GPUs and CPUs

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Object oriented DBMS

Relational DBMS

Graph DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
RDF store

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

Technical documentation

docs.atoti.io

docs.kinetica.com

docs.snowflake.net/manuals/index.html

spark.apache.org/docs/latest/sql-programming-guide.html

terminusdb.github.io/terminusdb/#

Developer

ActiveViam

Kinetica

Snowflake Computing Inc.

Apache Software Foundation

DataChemist Ltd.

Initial release

2012

2014

2018

Current release

7.1, August 2021

3.5.0 ( 2.13), September 2023

11.0.0, January 2023

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

Apache 2.0

Open Source

GPL V3

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

C, C++

Scala

Prolog, Rust

Server operating systems

Linux

hosted

Linux
OS X
Windows

Linux

Data scheme

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

Multidimensional Expressions (MDX)

SQL-like DML and DDL statements

yes

SQL-like DML and DDL statements

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Java
Python
R
Scala

JavaScript
Python

Server-side scripts

Stored procedures

Python

user defined functions

yes

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

Sharding, horizontal partitioning

Sharding

yes

yes, utilizing Spark Core

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

User concepts

Access control

Access rights for users and roles on table level

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

Role-based access control

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