DBMS > Apache Impala vs. Datomic vs. DuckDB vs. Transwarp Hippo

System Properties Comparison Apache Impala vs. Datomic vs. DuckDB vs. Transwarp Hippo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Relational DBMS

Vector DBMS

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	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	5.61
Rank	#60	Overall
	#34	Relational DBMS

Score	0.00
Rank	#385	Overall
	#16	Vector DBMS

Website

impala.apache.org

www.datomic.com

duckdb.org

www.transwarp.cn/en/subproduct/hippo

Technical documentation

impala.apache.org/impala-docs.html

docs.datomic.com

duckdb.org/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Cognitect

Initial release

2013

2012

2018

2023

Current release

4.1.0, June 2022

1.0.7180, July 2024

1.0.0, June 2024

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

limited edition free

Open Source

MIT License

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++

Java, Clojure

C++

Server operating systems

Linux

All OS with a Java VM

server-less

Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

RESTful HTTP API

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

C++
Java
Python

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

none

But extensive use of caching in the application peers

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

But extensive use of caching in the application peers

none

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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

Role based access control and fine grained access rights

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

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

Cloudera brings Apache Iceberg data lake format to its Data Platform
30 June 2022, SiliconANGLE News

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

Brazil’s Nubank Acquires US Software Firm Cognitect
30 July 2020, Nearshore Americas

Lucas Cavalcanti on Using Clojure, Microservices, Hexagonal Architecture and Public Cloud at Nubank
16 August 2021, InfoQ.com

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

Nubank acquires US company; PayPal studies cryptocurrencies
24 July 2020, iupana.com

Zoona Case Study
16 December 2017, AWS Blog

provided by Google News

My First Billion (of Rows) in DuckDB
1 May 2024, Towards Data Science

TigerEye Open Sources DuckDB.dart
15 August 2024, Datanami

LLM-Assisted Translation From Postgres to SQLite and DuckDB
16 September 2024, The New Stack

DuckDB: The tiny but powerful analytics database
15 May 2024, InfoWorld

TigerEye releases open-source DuckDB.dart to simplify data-intensive application development
15 August 2024, SiliconANGLE News

provided by Google News

10 top vector database options for similarity searches
8 August 2024, TechTarget

provided by Google News

Share this page