DBMS > Apache Impala vs. Google Cloud Spanner vs. SurrealDB

System Properties Comparison Apache Impala vs. Google Cloud Spanner vs. SurrealDB

Please select another system to include it in the comparison.

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.

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Relational DBMS

Document store
Graph DBMS

Secondary database models

Document store

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

Score	11.68
Rank	#41	Overall
	#25	Relational DBMS

Score	2.56
Rank	#97	Overall
	#50	Relational DBMS

Score	1.08
Rank	#176	Overall
	#30	Document stores
	#16	Graph DBMS

Website

impala.apache.org

cloud.google.com/spanner

surrealdb.com

Technical documentation

impala.apache.org/impala-docs.html

cloud.google.com/spanner/docs

surrealdb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Google

SurrealDB Ltd

Initial release

2013

2017

2022

Current release

4.1.0, June 2022

v1.5.0, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

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++

Rust

Server operating systems

Linux

hosted

Linux
macOS
Windows

Data scheme

yes

schema-free

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 DML and DDL statements

yes

Query statements complying to ANSI 2011

SQL-like query language

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
RESTful HTTP API
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
JavaScript (Node.js)
Python

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication with 3 replicas for regional instances.

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

Foreign keys

Referential integrity

yes

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

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.

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)

yes, based on authentication and database rules

More information provided by the system vendor

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SD Times

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Cloudera brings Apache Iceberg data lake format to its Data Platform
30 June 2022, SiliconANGLE

Apache Doris Analytical Database Graduates from Apache Incubator
20 June 2022, datanami.com

Apache Iceberg is now available on the Cloudera Data Platform
4 July 2022, techzine.eu

provided by Google News

Google Cloud Introduces HDD Tier for Spanner Database, Cutting Cold Storage Costs by 80%
22 March 2025, infoq.com

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

Google Cloud Spanner gets dual-region configuration option
23 July 2024, InfoWorld

Google Cloud adds graph and vector search features to Spanner database
2 August 2024, techzine.eu

Google Releases Spanner Graph into General Availability
19 February 2025, infoq.com

provided by Google News

SurrealDB Launches Surreal Cloud, a Fully Managed Database Service That Tackles the Complexity Issues Faced by Developer Teams
7 December 2024, insideAI News

SurrealDB Empowers Developers to Build Applications with the Launch of SurrealDB University
15 October 2024, Business Wire

SurrealDB's Surreal Cloud debuts on AWS S3 for scalable multimodel database as a service
4 December 2024, SiliconANGLE

SurrealDB is helping developers consolidate their databases
18 June 2024, TechCrunch

London-based SurrealDB secures over €18.6 million aiming to disrupt database technology
18 June 2024, EU-Startups

provided by Google News

Share this page