DBMS > Apache Impala vs. EXASOL vs. Hazelcast vs. ToroDB

System Properties Comparison Apache Impala vs. EXASOL vs. Hazelcast vs. ToroDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

A widely adopted in-memory data grid

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

Key-value store

Document store

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	6.87
Rank	#55	Overall
	#6	Key-value stores

Website

impala.apache.org

www.exasol.com

hazelcast.com

github.com/torodb/server

Technical documentation

impala.apache.org/impala-docs.html

www.exasol.com/resources

hazelcast.org/imdg/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Exasol

Hazelcast

8Kdata

Initial release

2013

2000

2008

2016

Current release

4.1.0, June 2022

5.3.6, November 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

Linux

All OS with a Java VM

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

.Net
JDBC
ODBC
WebSocket

JCache
JPA
Memcached protocol
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Java
Lua
Python
R

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

yes

Event Listeners, Executor Services

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Replicated Map

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users, groups and roles according to SQL-standard

Role-based access control

Access rights for users and roles

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More resources

Recent citations in the news

Apache Impala becomes Top-Level Project
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