DBMS > Datastax Enterprise vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB vs. Riak KV vs. Snowflake

System Properties Comparison Datastax Enterprise vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB vs. Riak KV vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Fully managed big data interactive analytics platform

Widely used in-process key-value store

Distributed, fault tolerant key-value store

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Wide column store

Relational DBMS

column oriented

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector 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	5.93
Rank	#56	Overall
	#4	Wide column stores

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.datastax.com/products/datastax-enterprise

azure.microsoft.com/services/data-explorer

www.oracle.com/database/technologies/related/berkeleydb.html

www.snowflake.com

Technical documentation

docs.datastax.com

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

docs.oracle.com/cd/E17076_05/html/index.html

www.tiot.jp/riak-docs/riak/kv/latest

docs.snowflake.net/manuals/index.html

Developer

DataStax

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

OpenSource, formerly Basho Technologies

Snowflake Computing Inc.

Initial release

2011

2019

1994

2009

2014

Current release

6.8, April 2020

cloud service with continuous releases

18.1.40, May 2020

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

commercial license available

Open Source

Apache version 2, commercial enterprise edition

commercial

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.

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

Implementation language

Java

C, Java, C++ (depending on the Berkeley DB edition)

Erlang

Server operating systems

Linux
OS X

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X

hosted

Data scheme

schema-free

Fixed schema with schema-less datatypes (dynamic)

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

only with the Berkeley DB XML edition

yes

Secondary indexes

yes

all fields are automatically indexed

yes

restricted

SQL

Support of SQL

SQL-like DML and DDL statements (CQL); Spark SQL

Kusto Query Language (KQL), SQL subset

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

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

HTTP API
Native Erlang Interface

CLI Client
JDBC
ODBC

Supported programming languages

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

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

Erlang

user defined functions

Triggers

yes

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

yes

only for the SQL API

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

Implicit feature of the cloud service

none

Sharding

no "single point of failure"

yes

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware, advanced replication for edge computing

yes

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

Source-replica replication

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

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 for users can be defined per object

Azure Active Directory Authentication

yes, using Riak Security

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more

Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
» more

Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
» more

Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more

Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more

Licensing and pricing models

Annual subscription
» more

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.