DBMS > Apache Impala vs. BigchainDB vs. Datomic vs. ITTIA

System Properties Comparison Apache Impala vs. BigchainDB vs. Datomic vs. ITTIA

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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

Edge Time Series DBMS with Real-Time Stream Processing

Primary database model

Secondary database models

Document store

Relational DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

bigchaindb.readthedocs.io/en/latest

docs.datomic.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Cognitect

ITTIA L.L.C.

Initial release

2013

2016

2012

2007

Current release

4.1.0, June 2022

1.0.7075, December 2023

8.7

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

AGPL v3

commercial

limited edition free

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Python

Java, Clojure

C and C++

Server operating systems

Linux

All OS with a Java VM

Linux
Windows

Data scheme

yes

schema-free

yes

Fixed schema

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

yes

APIs and other access methods

JDBC
ODBC

CLI Client
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

Go
Haskell
Java
JavaScript
Python
Ruby

Clojure
Java

C
C++
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Transaction Functions

yes

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

But extensive use of caching in the application peers

yes

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

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

yes

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

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

Database file passwords

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More resources

Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

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28 November 2017, Datanami

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27 September 2016, CoinDesk

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13 February 2016, CoinReport

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