DBMS > Apache Impala vs. Blueflood vs. Datomic vs. EventStoreDB

System Properties Comparison Apache Impala vs. Blueflood vs. Datomic vs. EventStoreDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Scalable TimeSeries DBMS based on Cassandra

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Primary database model

Secondary database models

Document store

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	0.06
Rank	#352	Overall
	#36	Time Series DBMS

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	1.07
Rank	#181	Overall
	#1	Event Stores

Website

Technical documentation

impala.apache.org/impala-docs.html

github.com/rax-maas/blueflood/wiki

docs.datomic.com

developers.eventstore.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Rackspace

Cognitect

Event Store Limited

Initial release

2013

2012

Current release

4.1.0, June 2022

1.0.7180, July 2024

21.2, February 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

limited edition free

Open Source

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

Java, Clojure

Server operating systems

Linux

Linux
OS X

All OS with a Java VM

Linux
Windows

Data scheme

yes

predefined scheme

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

HTTP REST

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Transaction Functions

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

But extensive use of caching in the application peers

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

But extensive use of caching in the application peers

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

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More resources

Recent citations in the news

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30 June 2022, SiliconANGLE News

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16 August 2021, InfoQ.com

Brazil’s Nubank acquires US software firm Cognitect, creator of Clojure and Datomic
24 July 2020, LatamList

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