DBMS > Apache Impala vs. Microsoft Azure Synapse Analytics vs. ToroDB vs. YottaDB

System Properties Comparison Apache Impala vs. Microsoft Azure Synapse Analytics vs. ToroDB vs. YottaDB

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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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

Document store

Key-value store

Secondary database models

Document store

Relational DBMS

using the Octo plugin

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

impala.apache.org

azure.microsoft.com/services/synapse-analytics

github.com/torodb/server

yottadb.com

Technical documentation

impala.apache.org/impala-docs.html

docs.microsoft.com/azure/synapse-analytics

yottadb.com/resources/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Microsoft

8Kdata

YottaDB, LLC

Initial release

2013

2016

2001

Current release

4.1.0, June 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

AGPL-V3

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

Linux

hosted

All OS with a Java 7 VM

Docker
Linux

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

by using the Octo plugin

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

C#
Java
PHP

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Source-replica replication

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

optimistic locking

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

yes

Access rights for users and roles

Users and groups based on OS-security mechanisms

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More resources

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