DBMS > Cachelot.io vs. Geode vs. Microsoft Azure Data Explorer vs. RocksDB vs. TypeDB

System Properties Comparison Cachelot.io vs. Geode vs. Microsoft Azure Data Explorer vs. RocksDB vs. TypeDB

Editorial information provided by DB-Engines

Name

Description

In-memory caching system

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Fully managed big data interactive analytics platform

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

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Key-value store

Relational DBMS

column oriented

Key-value store

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

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	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

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

Score	0.70
Rank	#230	Overall
	#20	Graph DBMS
	#106	Relational DBMS

Website

cachelot.io

geode.apache.org

azure.microsoft.com/services/data-explorer

rocksdb.org

typedb.com

Technical documentation

geode.apache.org/docs

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

github.com/facebook/rocksdb/wiki

typedb.com/docs

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Microsoft

Facebook, Inc.

Vaticle

Initial release

2015

2002

2019

2013

2016

Current release

1.1, February 2017

cloud service with continuous releases

9.2.1, May 2024

2.26.3, January 2024

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

BSD

Open Source

GPL Version 3, commercial licenses available

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++

Java

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

the JDK (8 or later) is also required

hosted

Linux

Linux
OS X
Windows

Data scheme

schema-free

Fixed schema with schema-less datatypes (dynamic)

schema-free

yes

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language (OQL)

Kusto Query Language (KQL), SQL subset

APIs and other access methods

Memcached protocol

Java Client API
Memcached protocol
RESTful HTTP API

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

C++ API
Java API

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

.Net
All JVM based languages
C++
Groovy
Java
Scala

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

C
C++
Go
Java
Perl
Python
Ruby

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

user defined functions

Yes, possible languages: KQL, Python, R

Triggers

yes

Cache Event Listeners

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

horizontal partitioning

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

yes

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

yes

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

substituted by the relationship feature

Transaction concepts

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

yes, on a single node

yes

ACID

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 per client and object definable

Azure Active Directory Authentication

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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