DBMS > Apache Impala vs. Snowflake vs. Splunk vs. SQLite vs. TiDB

System Properties Comparison Apache Impala vs. Snowflake vs. Splunk vs. SQLite vs. TiDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

Analytics Platform for Big Data

Widely used embeddable, in-process RDBMS

TiDB is an open source distributed SQL database that supports Hybrid Transactional/Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.

Primary database model

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	4.25
Rank	#74	Overall
	#40	Relational DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

docs.snowflake.net/manuals/index.html

docs.splunk.com/Documentation/Splunk

www.sqlite.org/docs.html

docs.pingcap.com/tidb/stable

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Snowflake Computing Inc.

Splunk Inc.

Dwayne Richard Hipp

PingCAP, Inc.

Initial release

2013

2014

2003

2000

2016

Current release

4.1.0, June 2022

3.46.0 (23 May 2024), May 2024

8.1.0, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Limited free edition and free developer edition available

Open Source

Public Domain

Open Source

Apache 2.0

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.

TiDB Cloud: Fully-managed TiDB Service. Bring everything great about TiDB to the cloud.

Implementation language

C++

Go, Rust

Server operating systems

Linux

hosted

Linux
OS X
Solaris
Windows

server-less

Linux

Data scheme

yes

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

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

yes

Splunk Search Processing Language for search commands

yes

SQL-92 is not fully supported

yes

APIs and other access methods

JDBC
ODBC

CLI Client
JDBC
ODBC

HTTP REST

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

GORM
JDBC
ODBC
Proprietary protocol
SQLAlchemy

Supported programming languages

All languages supporting JDBC/ODBC

JavaScript (Node.js)
Python

C#
Java
JavaScript
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

yes

Triggers

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

none

horizontal partitioning (by key range)

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-source replication

none

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

with TiSpark Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

full support since version 6.6

Transaction concepts

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

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

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

Access rights for users and roles

Fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

TiDB is an advanced open-source, distributed SQL database for modern application...
» more

Competitive advantages

- HORIZONTAL SCALING : TiDB grants total transparency into your data workloads without...
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Typical application scenarios

TiDB is ideal for transactional applications that require extreme scalability and...
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Key customers

Block, Pinterest, Catalyst, Bolt, Flipkart, Capcom, Shopee (E-commerce), JD Cloud...
» more

Market metrics

34K+ GitHub stars 5K+ members in TiDB Community Slack 1K+ community contributors...
» more

Licensing and pricing models

TiDB Community : Free open source software (Apache 2.0) TiDB Self-Hosted : Enterprise...
» more

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