DBMS > RavenDB vs. SAP HANA vs. SingleStore vs. Spark SQL

System Properties Comparison RavenDB vs. SAP HANA vs. SingleStore vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

Open Source Operational and Transactional Enterprise NoSQL Document Database

In-memory, column based data store. Available as appliance or cloud service

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Document store

Relational DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

ravendb.net

www.sap.com/products/hana.html

www.singlestore.com

spark.apache.org/sql

Technical documentation

ravendb.net/docs

help.sap.com/hana

docs.singlestore.com

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Hibernating Rhinos

SAP

SingleStore Inc.

Apache Software Foundation

Initial release

2010

2013

2014

Current release

5.4, July 2022

2.0 SPS07 (April 4, 2023), April 2023

8.5, January 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

AGPL version 3, commercial license available

commercial

free developer edition available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

C++, Go

Scala

Server operating systems

Linux
macOS
Raspberry Pi
Windows

Appliance or cloud-service

Linux

64 bit version required

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (RQL)

yes

but no triggers and foreign keys

SQL-like DML and DDL statements

APIs and other access methods

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

JDBC
ODBC

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

JDBC
ODBC

Supported programming languages

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Bash
C
C#
Java
JavaScript (Node.js)
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

SQLScript, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

hash partitioning

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Authorization levels configured per client per database

yes

Fine grained access control via users, groups and roles

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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Key customers

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Market metrics

Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

F ree Tier and Enterprise Edition
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