DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Apache Impala vs. HBase vs. Microsoft Azure Data Explorer vs. Tarantool
System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Apache Impala vs. HBase vs. Microsoft Azure Data Explorer vs. Tarantool
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| Name | Alibaba Cloud AnalyticDB for PostgreSQL  former name was HybridDB Xexclude from comparison | Apache Impala Xexclude from comparison | HBase Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | Tarantool Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum | Analytic DBMS for Hadoop | Wide-column store based on Apache Hadoop and on concepts of BigTable | Fully managed big data interactive analytics platform | In-memory computing platform with a flexible data schema for efficiently building high-performance applications | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Relational DBMS | Relational DBMS | Wide column store | Relational DBMS column oriented | Document store Key-value store Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Document store | Document store If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell Event Store this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)Spatial DBMS Search engine support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engineTime Series DBMS see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | Spatial DBMS with Tarantool/GIS extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | www.alibabacloud.com/product/hybriddb-postgresql | impala.apache.org | hbase.apache.org | azure.microsoft.com/services/data-explorer | www.tarantool.io | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview | impala.apache.org/impala-docs.html | hbase.apache.org/book.html | docs.microsoft.com/en-us/azure/data-explorer | www.tarantool.io/en/doc | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group | Apache Software Foundation Apache top-level project, originally developed by Cloudera | Apache Software Foundation Apache top-level project, originally developed by Powerset | Microsoft | VK | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2016 | 2013 | 2008 | 2019 | 2008 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 4.1.0, June 2022 | 2.3.4, January 2021 | cloud service with continuous releases | 2.10.0, May 2022 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial | Open Source Apache Version 2 | Open Source Apache version 2 | commercial | Open Source BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | yes | no | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | C++ | Java | C and C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | hosted | Linux | Linux Unix Windows using Cygwin | hosted | BSD Linux macOS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes | yes | schema-free, schema definition possible | Fixed schema with schema-less datatypes (dynamic) | Flexible data schema: relational definition for tables with ability to store json-like documents in columns | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes | options to bring your own types, AVRO | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | string, double, decimal, uuid, integer, blob, boolean, datetime | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | no | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | no | all fields are automatically indexed | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | yes | SQL-like DML and DDL statements | no | Kusto Query Language (KQL), SQL subset | Full-featured ANSI SQL support | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | JDBC ODBC | JDBC ODBC | Java API RESTful HTTP API Thrift | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | Open binary protocol | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | C Java Perl Python R | All languages supporting JDBC/ODBC | C C# C++ Groovy Java PHP Python Scala | .Net Go Java JavaScript (Node.js) PowerShell Python R | C C# C++ Erlang Go Java JavaScript Lua Perl PHP Python Rust | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | yes | yes user defined functions and integration of map-reduce | yes Coprocessors in Java | Yes, possible languages: KQL, Python, R | Lua, C and SQL stored procedures | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes | no | yes | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes, before/after data modification events, on replication events, client session events | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding Implicit feature of the cloud service | Sharding | Sharding | Sharding Implicit feature of the cloud service | Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | yes Implicit feature of the cloud service | selectable replication factor | Multi-source replication Source-replica replication | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Asynchronous replication with multi-master option Configurable replication topology (full-mesh, chain, star) Synchronous quorum replication (with Raft) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no | yes query execution via MapReduce | yes | Spark connector (open source): github.com/Azure/azure-kusto-spark | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Eventual Consistency | Immediate Consistency or Eventual Consistency | Eventual Consistency Immediate Consistency | Casual consistency across sharding partitions Eventual consistency within replicaset partition when using asyncronous replicationImmediate Consistency within single instance Sequential consistency including linearizable read within replicaset partition when using Raft | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | yes | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | Single row ACID (across millions of columns) | no | ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes, cooperative multitasking | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes | yes, write ahead logging | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | no | yes | no | yes, full featured in-memory storage engine with persistence | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | fine grained access rights according to SQL-standard | Access rights for users, groups and roles based on Apache Sentry and Kerberos | Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC | Azure Active Directory Authentication | Access Control Lists Mutual TLS authentication for Tarantol Enterprise Password based authentication Role-based access control (RBAC) and LDAP for Tarantol Enterprise Users and Roles | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Alibaba Cloud AnalyticDB for PostgreSQL former name was HybridDB | Apache Impala | HBase | Microsoft Azure Data Explorer | Tarantool | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | Cloudera's HBase PaaS offering now supports Complex Transactions Why is Hadoop not listed in the DB-Engines Ranking? | Data processing speed and reliability: in-memory synchronous replication Two Critical Flaws Found in Alibaba Cloud's PostgreSQL Databases Accidental ‘write’ Permissions In Alibaba PostgreSQL Let Attackers Access Sensitive Data Alibaba News Roundup: Disney, Freshippo Launch Collaboration Alibaba Cloud to spur AI innovation with upcoming Singapore hackathon in March | KrASIA Experts disclosed two critical flaws in Alibaba cloud database services provided by Google News Apache Impala 4 Supports Operator Multi-Threading Cloudera Bringing Impala to AWS Cloud Apache Impala becomes Top-Level Project Apache Doris just 'graduated': Why care about this SQL data warehouse Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop provided by Google News Less Components, Higher Performance: Apache Doris instead of ClickHouse, MySQL, Presto, and HBase HBase: The database big data left behind Monitor Apache HBase on Amazon EMR using Amazon Managed Service for Prometheus and Amazon Managed ... HydraBase – The evolution of HBase@Facebook - Engineering at Meta A Look At HBase, the NoSQL Database Built on Hadoop provided by Google News Azure Data Explorer: Log and telemetry analytics benchmark Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog Controlling costs in Azure Data Explorer using down-sampling and aggregation Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services Log and Telemetry Analytics Performance Benchmark provided by Google News Deploying Tarantool Cartridge applications with zero effort (Part 1) VShard — horizontal scaling in Tarantool Accelerating PHP connectors for Tarantool using Async, Swoole, and Parallel provided by Google News | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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