DBMS > Citus vs. Rockset vs. SAP SQL Anywhere vs. Snowflake vs. Solr

System Properties Comparison Citus vs. Rockset vs. SAP SQL Anywhere vs. Snowflake vs. Solr

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Secondary database models

Document store

Relational DBMS
Search engine

Spatial DBMS

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

www.citusdata.com

rockset.com

www.sap.com/products/technology-platform/sql-anywhere.html

www.snowflake.com

solr.apache.org

Technical documentation

docs.citusdata.com

docs.rockset.com

help.sap.com/docs/SAP_SQL_Anywhere

docs.snowflake.net/manuals/index.html

solr.apache.org/resources.html

Developer

Rockset

SAP

formerly Sybase

Snowflake Computing Inc.

Apache Software Foundation

Initial release

2010

2019

1992

2014

2006

Current release

8.1, December 2018

17, July 2015

9.6.0, April 2024

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

commercial

Open Source

Apache Version 2

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

Server operating systems

Linux

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

hosted

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

schema-free

yes

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

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

dynamic typing

yes

supports customizable data types and automatic typing

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

specific XML type available, but no XML query functionality

ingestion from XML files supported

yes

Secondary indexes

yes

all fields are automatically indexed

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

standard, with numerous extensions

Read-only SQL queries, including JOINs

yes

Solr Parallel SQL Interface

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST

ADO.NET
HTTP API
JDBC
ODBC

CLI Client
JDBC
ODBC

Java API
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Go
Java
JavaScript (Node.js)
Python

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

JavaScript (Node.js)
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes, in C/C++, Java, .Net or Perl

user defined functions

Java plugins

Triggers

yes

similar concept for controling cloud resources

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

none

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

yes

Source-replica replication

Database mirroring

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

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

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

fine grained access rights according to SQL-standard

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

yes

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