DBMS > Apache Impala vs. Google Cloud Spanner vs. Stardog vs. TDengine

System Properties Comparison Apache Impala vs. Google Cloud Spanner vs. Stardog vs. TDengine

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Time Series DBMS and big data platform

Primary database model

Relational DBMS

Graph DBMS
RDF store

Time Series DBMS

Secondary database models

Document store

Relational DBMS

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Score	2.48
Rank	#107	Overall
	#9	Time Series DBMS

Website

impala.apache.org

cloud.google.com/spanner

www.stardog.com

github.com/taosdata/TDengine
tdengine.com

Technical documentation

impala.apache.org/impala-docs.html

cloud.google.com/spanner/docs

docs.stardog.com

docs.tdengine.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Google

Stardog-Union

TDEngine, previously Taos Data

Initial release

2013

2017

2010

2019

Current release

4.1.0, June 2022

7.3.0, May 2020

3.0, August 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

AGPL V3, also commercial editions available

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

Linux
macOS
Windows

Linux
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like DML and DDL statements

yes

Query statements complying to ANSI 2011

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

Standard SQL with extensions for time-series applications

APIs and other access methods

JDBC
ODBC

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

JDBC
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
JavaScript (Node.js)
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication with 3 replicas for regional instances.

Multi-source replication in HA-Cluster

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

Strict serializable isolation

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and roles

yes

More information provided by the system vendor

Specific characteristics

TDengine™ is a time-series database designed to help traditional industries overcome...
» more

Competitive advantages

High Performance at Any Scale: With its distributed scalable architecture that grows...
» more

Typical application scenarios

TDengine is purpose-built for Industry 4.0 and the Industrial IoT (IIoT) and particularly...
» more

Market metrics

TDengine has garnered over 23,000 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

TDengine OSS is free, open-source software released under the AGPLv3. TDengine Enterprise...
» more

News

Optimize Data Consolidation for Multi-Site Renewable Energy Operations
9 September 2024

Connect Power BI to TDengine
6 September 2024

Using Streams and Subscriptions for Alerting
5 September 2024

Solar Panel Monitoring: OPC UA Ingestion
2 September 2024

Time-Series Databases: A Game Changer for the Renewable Energy Industry
30 August 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

Recent citations in the news

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29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

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30 June 2022, SiliconANGLE News

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12 March 2017, Uber

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27 October 2017, KDnuggets

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1 August 2024, InfoQ.com

New features make Google's Spanner a database for AI
1 August 2024, TechTarget

Google Cloud expands its database portfolio with new AI capabilities
1 August 2024, TechCrunch

provided by Google News

TDengine Cloud released to developers
19 October 2022, App Developer Magazine

TDengine Brings Open Source Time-Series Database to Kubernetes
19 April 2023, Cloud Native Now

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

MindsDB is now the leading and fastest growing applied ML platform in the world
3 November 2022, PR Newswire

provided by Google News

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