DBMS > Rockset vs. SiteWhere vs. Snowflake vs. Splice Machine vs. XTDB

System Properties Comparison Rockset vs. SiteWhere vs. Snowflake vs. Splice Machine vs. XTDB

Editorial information provided by DB-Engines

Name

Description

A scalable, reliable search and analytics service in the cloud, built on RocksDB

M2M integration platform for persisting/querying time series data

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

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

Primary database model

Secondary database models

Relational DBMS
Search engine

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

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

rockset.com

github.com/sitewhere/sitewhere

www.snowflake.com

splicemachine.com

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

Technical documentation

docs.rockset.com

sitewhere1.sitewhere.io/index.html

docs.snowflake.net/manuals/index.html

splicemachine.com/how-it-works

www.xtdb.com/docs

Developer

Rockset

SiteWhere

Snowflake Computing Inc.

Splice Machine

Juxt Ltd.

Initial release

2019

2010

2014

2019

Current release

3.1, March 2021

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

MIT License

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

Clojure

Server operating systems

hosted

Linux
OS X
Windows

hosted

Linux
OS X
Solaris
Windows

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

Data scheme

schema-free

predefined scheme

yes

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

yes

schema-free

Typing

predefined data types such as float or date

dynamic typing

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.

ingestion from XML files supported

yes

Secondary indexes

all fields are automatically indexed

yes

SQL

Support of SQL

Read-only SQL queries, including JOINs

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP REST

CLI Client
JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

HTTP REST
JDBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

yes

Java

Triggers

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

based on HBase

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on HBase

yes

Multi-source replication
Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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 and organizations can be defined via Rockset console

Users with fine-grained authorization concept

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

Access rights for users, groups and roles according to SQL-standard

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