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

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

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

GridGain is an in-memory computing platform, built on Apache Ignite

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

Analytics Platform for Big Data

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

Key-value store
Relational DBMS

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	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	4.25
Rank	#74	Overall
	#40	Relational DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

www.gridgain.com/docs/index.html

docs.snowflake.net/manuals/index.html

docs.splunk.com/Documentation/Splunk

docs.pingcap.com/tidb/stable

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

GridGain Systems, Inc.

Snowflake Computing Inc.

Splunk Inc.

PingCAP, Inc.

Initial release

2013

2007

2014

2003

2016

Current release

4.1.0, June 2022

GridGain 8.5.1

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

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++

Java, C++, .Net

Go, Rust

Server operating systems

Linux

Linux
OS X
Solaris
Windows

hosted

Linux
OS X
Solaris
Windows

Linux

Data scheme

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

ANSI-99 for query and DML statements, subset of DDL

yes

Splunk Search Processing Language for search commands

yes

APIs and other access methods

JDBC
ODBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

CLI Client
JDBC
ODBC

HTTP REST

GORM
JDBC
ODBC
Proprietary protocol
SQLAlchemy

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

C#
Java
JavaScript
PHP
Python
Ruby

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

yes (compute grid and cache interceptors can be used instead)

user defined functions

yes

Triggers

yes (cache interceptors and events)

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

horizontal partitioning (by key range)

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes (replicated cache)

yes

Multi-source replication

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 (compute grid and hadoop accelerator)

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

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

Security Hooks for custom implementations

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...
» more

Typical application scenarios

TiDB is ideal for transactional applications that require extreme scalability and...
» more

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.