DBMS > EJDB vs. Kinetica vs. Machbase Neo vs. Snowflake

System Properties Comparison EJDB vs. Kinetica vs. Machbase Neo vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Fully vectorized database across both GPUs and CPUs

TimeSeries DBMS for AIoT and BigData

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

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

github.com/Softmotions/ejdb

www.kinetica.com

machbase.com

www.snowflake.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

docs.kinetica.com

machbase.com/dbms

docs.snowflake.net/manuals/index.html

Developer

Softmotions

Kinetica

Machbase

Snowflake Computing Inc.

Initial release

2012

2013

2014

Current release

7.1, August 2021

V8.0, August 2023

License

Commercial or Open Source

Open Source

GPLv2

commercial

free test 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++

Server operating systems

server-less

Linux

Linux
macOS
Windows

hosted

Data scheme

schema-free

yes

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

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

SQL-like DML and DDL statements

SQL-like query language

yes

APIs and other access methods

in-process shared library

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

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

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

selectable replication factor

yes

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

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write 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

GPU vRAM or System RAM

yes

volatile and lookup table

User concepts

Access control

Access rights for users and roles on table level

simple password-based access control

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

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