DBMS > Apache Impala vs. H2GIS vs. Microsoft Azure Table Storage vs. Sqrrl vs. XTDB

System Properties Comparison Apache Impala vs. H2GIS vs. Microsoft Azure Table Storage vs. Sqrrl vs. XTDB

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

Analytic DBMS for Hadoop

Spatial extension of H2

A Wide Column Store for rapid development using massive semi-structured datasets

Adaptable, secure NoSQL built on Apache Accumulo

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Spatial DBMS

Wide column store

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Secondary database models

Document store

Relational DBMS

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	0.05
Rank	#372	Overall
	#7	Spatial DBMS

Score	4.92
Rank	#73	Overall
	#6	Wide column stores

Score	0.09
Rank	#351	Overall
	#47	Document stores

Website

impala.apache.org

www.h2gis.org

azure.microsoft.com/en-us/services/storage/tables

sqrrl.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

impala.apache.org/impala-docs.html

www.h2gis.org/docs/home

www.xtdb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

CNRS

Microsoft

Amazon

originally Sqrrl Data, Inc.

Juxt Ltd.

Initial release

2013

2012

2019

Current release

4.1.0, June 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

LGPL 3.0

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Java

Clojure

Server operating systems

Linux

hosted

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC

Java

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

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Sharding

making use of Hadoop

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

based on H2

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

selectable replication factor

making use of Hadoop

yes, each node contains all data

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

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

Atomic updates per row, document, or graph entity

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

yes

based on H2

Access rights based on private key authentication or shared access signatures

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources

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