DBMS > Datastax Enterprise vs. Netezza vs. SiriDB vs. Typesense vs. XTDB

System Properties Comparison Datastax Enterprise vs. Netezza vs. SiriDB vs. Typesense vs. XTDB

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.

Data warehouse and analytics appliance part of IBM PureSystems

Open Source Time Series DBMS

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

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

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	5.93
Rank	#56	Overall
	#4	Wide column stores

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	0.76
Rank	#219	Overall
	#14	Search engines

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.datastax.com/products/datastax-enterprise

www.ibm.com/products/netezza

siridb.com

typesense.org

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

Technical documentation

Developer

DataStax

IBM

Cesbit

Juxt Ltd.

Initial release

2011

2000

2017

2015

2019

Current release

6.8, April 2020

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

GPL V3

Open Source

MIT License

Cloud-based only

Only available as a cloud service

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++

Clojure

Server operating systems

Linux
OS X

Linux

included in appliance

Linux

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

Data scheme

schema-free

yes

schema-free

pre-defined schema optional

schema-free

Typing

predefined data types such as float or date

yes

Numeric data

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.

Secondary indexes

yes

SQL

Support of SQL

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

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

JDBC
ODBC
OLE DB

HTTP API

RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

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

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

yes

Multi-source replication using RAFT

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Foreign keys

Referential integrity

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

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 can be defined per object

Users with fine-grained authorization concept

simple rights management via user accounts

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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