DBMS > Immudb vs. Microsoft Azure Data Explorer vs. Netezza vs. RocksDB

System Properties Comparison Immudb vs. Microsoft Azure Data Explorer vs. Netezza vs. RocksDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Fully managed big data interactive analytics platform

Data warehouse and analytics appliance part of IBM PureSystems

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

column oriented

Secondary database models

Relational DBMS

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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

Score	0.31
Rank	#295	Overall
	#42	Key-value stores

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

github.com/codenotary/immudb
immudb.io

azure.microsoft.com/services/data-explorer

www.ibm.com/products/netezza

rocksdb.org

Technical documentation

docs.immudb.io

docs.microsoft.com/en-us/azure/data-explorer

github.com/facebook/rocksdb/wiki

Developer

Codenotary

Microsoft

IBM

Facebook, Inc.

Initial release

2020

2019

2000

2013

Current release

1.2.3, April 2022

cloud service with continuous releases

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

BSD

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

C++

Server operating systems

BSD
Linux
macOS
Solaris
Windows
z/OS

hosted

Linux

included in appliance

Linux

Data scheme

schema-free

Fixed schema with schema-less datatypes (dynamic)

yes

schema-free

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

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.

yes

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like syntax

Kusto Query Language (KQL), SQL subset

yes

APIs and other access methods

gRPC protocol
PostgreSQL wire protocol

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

JDBC
ODBC
OLE DB

C++ API
Java API

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
Python

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

yes

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

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

Azure Active Directory Authentication

Users with fine-grained authorization concept

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.