DBMS > Apache Impala vs. RavenDB vs. Snowflake vs. TimesTen

System Properties Comparison Apache Impala vs. RavenDB vs. Snowflake vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	2.68
Rank	#102	Overall
	#19	Document stores

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

impala.apache.org

ravendb.net

www.snowflake.com

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

Technical documentation

impala.apache.org/impala-docs.html

ravendb.net/docs

docs.snowflake.net/manuals/index.html

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Hibernating Rhinos

Snowflake Computing Inc.

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2013

2010

2014

1998

Current release

4.1.0, June 2022

5.4, July 2022

Release 22.1

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

AGPL version 3, commercial license available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux

Linux
macOS
Raspberry Pi
Windows

hosted

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

yes

schema-free

yes

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

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (RQL)

yes

APIs and other access methods

JDBC
ODBC

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

CLI Client
JDBC
ODBC

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

All languages supporting JDBC/ODBC

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

JavaScript (Node.js)
Python

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

user defined functions

PL/SQL

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Immediate Consistency or Eventual Consistency depending on configuration

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

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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, groups and roles

based on Apache Sentry and Kerberos

Authorization levels configured per client per database

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

fine grained access rights according to SQL-standard

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