DBMS > Apache Impala vs. Cachelot.io vs. Databend vs. Lovefield vs. Stardog

System Properties Comparison Apache Impala vs. Cachelot.io vs. Databend vs. Lovefield vs. Stardog

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

In-memory caching system

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Embeddable relational database for web apps written in pure JavaScript

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

Primary database model

Secondary database models

Document store

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Trend Chart

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

impala.apache.org

cachelot.io

github.com/datafuselabs/databend
www.databend.com

google.github.io/lovefield

www.stardog.com

Technical documentation

impala.apache.org/impala-docs.html

docs.databend.com

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

docs.stardog.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Databend Labs

Google

Stardog-Union

Initial release

2013

2015

2021

2014

2010

Current release

4.1.0, June 2022

1.0.59, April 2023

2.1.12, February 2017

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Simplified BSD License

Open Source

Apache Version 2.0

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

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Rust

JavaScript

Java

Server operating systems

Linux

FreeBSD
Linux
OS X

hosted
Linux
macOS

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

tested with Chrome, Firefox, IE, Safari

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

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.

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

yes

SQL-like query language

via JavaScript builder pattern

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

APIs and other access methods

JDBC
ODBC

Memcached protocol

CLI Client
JDBC
RESTful HTTP API

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

All languages supporting JDBC/ODBC

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python
Rust

JavaScript

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

Using read-only observers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

using MemoryDB

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Users with fine-grained authorization concept, user roles

Access rights for users and roles

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More resources

Recent citations in the news

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