DBMS > Hive vs. Ignite vs. Microsoft Azure SQL Database vs. VoltDB vs. XTDB

System Properties Comparison Hive vs. Ignite vs. Microsoft Azure SQL Database vs. VoltDB vs. XTDB

Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Database as a Service offering with high compatibility to Microsoft SQL Server

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Document store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

hive.apache.org

ignite.apache.org

azure.microsoft.com/en-us/products/azure-sql/database

www.voltdb.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

apacheignite.readme.io/docs

docs.microsoft.com/en-us/azure/azure-sql

docs.voltdb.com

www.xtdb.com/docs

Developer

Apache Software Foundation

initially developed by Facebook

Apache Software Foundation

Microsoft

VoltDB Inc.

Juxt Ltd.

Initial release

2012

2015

2010

2019

Current release

3.1.3, April 2022

Apache Ignite 2.6

V12

11.3, April 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++, Java, .Net

C++

Java, C++

Clojure

Server operating systems

All OS with a Java VM

Linux
OS X
Solaris
Windows

hosted

Linux
OS X

for development

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

ANSI-99 for query and DML statements, subset of DDL

yes

only a subset of SQL 99

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC
Thrift

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC

Java API
JDBC
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

C++
Java
PHP
Python

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes (compute grid and cache interceptors can be used instead)

Transact SQL

Java

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes (replicated cache)

yes, with always 3 replicas available

Multi-source replication
Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

ACID

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

Snapshots and command logging

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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