DBMS > Ehcache vs. Kinetica vs. Lovefield vs. Snowflake vs. Stardog

System Properties Comparison Ehcache vs. Kinetica vs. Lovefield vs. Snowflake vs. Stardog

Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Fully vectorized database across both GPUs and CPUs

Embeddable relational database for web apps written in pure JavaScript

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Key-value store

Relational DBMS

Graph DBMS
RDF store

Secondary database models

Spatial DBMS
Time Series DBMS

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Trend Chart

Score	4.79
Rank	#66	Overall
	#8	Key-value stores

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Website

www.ehcache.org

www.kinetica.com

google.github.io/lovefield

www.snowflake.com

www.stardog.com

Technical documentation

www.ehcache.org/documentation

docs.kinetica.com

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.snowflake.net/manuals/index.html

docs.stardog.com

Developer

Terracotta Inc, owned by Software AG

Kinetica

Google

Snowflake Computing Inc.

Stardog-Union

Initial release

2009

2012

2014

2010

Current release

3.10.0, March 2022

7.1, August 2021

2.1.12, February 2017

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

Apache 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++

JavaScript

Java

Server operating systems

All OS with a Java VM

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

hosted

Linux
macOS
Windows

Data scheme

schema-free

yes

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

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

via JavaScript builder pattern

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JCache

JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

Java

C++
Java
JavaScript (Node.js)
Python

JavaScript

JavaScript (Node.js)
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

Cache Event Listeners

yes

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

Using read-only observers

similar concept for controling cloud resources

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Source-replica replication

none

yes

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

yes

User concepts

Access control

Access rights for users and roles on table level

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

Access rights for users and roles

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