DBMS > Apache Impala vs. Datomic vs. DolphinDB vs. ObjectBox

System Properties Comparison Apache Impala vs. Datomic vs. DolphinDB vs. ObjectBox

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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

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

Relational DBMS

Time Series DBMS

Object oriented DBMS

Secondary database models

Document store

Relational DBMS

Time Series DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

docs.datomic.com

docs.dolphindb.cn/en/help200/index.html

docs.objectbox.io

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Cognitect

DolphinDB, Inc

ObjectBox Limited

Initial release

2013

2012

2018

2017

Current release

4.1.0, June 2022

1.0.6735, June 2023

v2.00.4, January 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

limited edition free

commercial

free community version available

Open Source

Apache License 2.0

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++

C and C++

Server operating systems

Linux

All OS with a Java VM

Linux
Windows

Android
iOS
Linux
macOS
Windows

Data 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

SQL-like query language

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

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

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

But extensive use of caching in the application peers

yes

online/offline synchronization between client and server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

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

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)

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

Administrators, Users, Groups

yes

More information provided by the system vendor

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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 Bringing Impala to AWS Cloud
28 November 2017, Datanami

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

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24 June 2022, InfoWorld

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