DBMS > LevelDB vs. Microsoft Azure Data Explorer vs. OpenTSDB vs. RocksDB

System Properties Comparison LevelDB vs. Microsoft Azure Data Explorer vs. OpenTSDB vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Fully managed big data interactive analytics platform

Scalable Time Series DBMS based on HBase

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

Primary database model

column oriented

Secondary database models

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	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

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

Website

github.com/google/leveldb

azure.microsoft.com/services/data-explorer

opentsdb.net

rocksdb.org

Technical documentation

github.com/google/leveldb/blob/main/doc/index.md

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

opentsdb.net/docs/build/html/index.html

github.com/facebook/rocksdb/wiki

Developer

Google

Microsoft

currently maintained by Yahoo and other contributors

Facebook, Inc.

Initial release

2011

2019

2011

2013

Current release

1.23, February 2021

cloud service with continuous releases

9.2.1, May 2024

License

Commercial or Open Source

Open Source

BSD

commercial

Open Source

LGPL

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++

Java

C++

Server operating systems

Illumos
Linux
OS X
Windows

hosted

Linux
Windows

Linux

Data scheme

schema-free

Fixed schema with schema-less datatypes (dynamic)

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

numeric data for metrics, strings for tags

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

all fields are automatically indexed

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

APIs and other access methods

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

HTTP API
Telnet API

C++ API
Java API

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

Erlang
Go
Java
Python
R
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

selectable replication factor

based on HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

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