DBMS > Microsoft Azure Data Explorer vs. SAP HANA vs. Sphinx vs. Splice Machine vs. Tarantool
System Properties Comparison Microsoft Azure Data Explorer vs. SAP HANA vs. Sphinx vs. Splice Machine vs. Tarantool
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Name | Microsoft Azure Data Explorer Xexclude from comparison | SAP HANA Xexclude from comparison | Sphinx Xexclude from comparison | Splice Machine Xexclude from comparison | Tarantool Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Fully managed big data interactive analytics platform | In-memory, column based data store. Available as appliance or cloud service | Open source search engine for searching in data from different sources, e.g. relational databases | Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark | In-memory computing platform with a flexible data schema for efficiently building high-performance applications | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS column oriented | Relational DBMS | Search engine | Relational DBMS | Document store Key-value store Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | 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 engine Time Series DBMS see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | Document store Graph DBMS with SAP Hana, Enterprise Edition Spatial DBMS | Spatial DBMS with Tarantool/GIS extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | azure.microsoft.com/services/data-explorer | www.sap.com/products/hana.html | sphinxsearch.com | splicemachine.com | www.tarantool.io | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.microsoft.com/en-us/azure/data-explorer | help.sap.com/hana | sphinxsearch.com/docs | splicemachine.com/how-it-works | www.tarantool.io/en/doc | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Microsoft | SAP | Sphinx Technologies Inc. | Splice Machine | VK | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2019 | 2010 | 2001 | 2014 | 2008 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | cloud service with continuous releases | 2.0 SPS07 (April 4, 2023), April 2023 | 3.5.1, February 2023 | 3.1, March 2021 | 2.10.0, May 2022 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | commercial | Open Source GPL version 2, commercial licence available | Open Source AGPL 3.0, commercial license available | Open Source BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no also available as a cloud based service | no | no | 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 | Appliance or cloud-service | FreeBSD Linux NetBSD OS X Solaris Windows | Linux OS X Solaris Windows | BSD Linux macOS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | Fixed schema with schema-less datatypes (dynamic) | yes | yes | yes | 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 bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | yes | no | yes | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | all fields are automatically indexed | yes | yes full-text index on all search fields | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | Kusto Query Language (KQL), SQL subset | yes | SQL-like query language (SphinxQL) | yes | Full-featured ANSI SQL support | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | JDBC ODBC | Proprietary protocol | JDBC Native Spark Datasource ODBC | Open binary protocol | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net Go Java JavaScript (Node.js) PowerShell Python R | C++ unofficial client library Java Perl unofficial client library PHP Python Ruby unofficial client library | C# C++ Java JavaScript (Node.js) Python R Scala | C C# C++ Erlang Go Java JavaScript Lua Perl PHP Python Rust | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | Yes, possible languages: KQL, Python, R | SQLScript, R | no | yes Java | Lua, C and SQL stored procedures | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes | no | yes | 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 | yes | Sharding Partitioning is done manually, search queries against distributed index is supported | Shared Nothhing Auto-Sharding, Columnar Partitioning | 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. Replication either local, cross-facility or geo-redundant. | yes | none | Multi-source replication Source-replica replication | 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 | Spark connector (open source): github.com/Azure/azure-kusto-spark | no | no | Yes, via Full Spark Integration | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency | Immediate Consistency | Immediate Consistency | Casual consistency across sharding partitions Eventual consistency within replicaset partition when using asyncronous replication Immediate Consistency within single instance Sequential consistency including linearizable read within replicaset partition when using Raft | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID | no | ACID | 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, multi-version concurrency control (MVCC) | yes, cooperative multitasking | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes The original contents of fields are not stored in the Sphinx index. | 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 | yes | yes | yes, full featured in-memory storage engine with persistence | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Azure Active Directory Authentication | yes | no | Access rights for users, groups and roles according to SQL-standard | 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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Microsoft Azure Data Explorer | SAP HANA | Sphinx | Splice Machine | Tarantool | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | The DB-Engines ranking includes now search engines | Data processing speed and reliability: in-memory synchronous replication We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates Update records in a Kusto Database (public preview) Public Preview: Azure Data Explorer connector for Apache Flink Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints ... New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates provided by Google News Unlock new potential for your SAP workloads on Azure with these learning paths Combine the Power of AI with Business Context Using SAP HANA Cloud Vector Engine Accenture and SAP Accelerate Business Transformation with AI SAP customers may struggle to escape ECC before support shutters if they don't start now 5 New Google Cloud-SAP Products Launched At Sapphire For AI, HANA And Cloud provided by Google News Switching From Sphinx to MkDocs Documentation — What Did I Gain and Lose Manticore is a Faster Alternative to Elasticsearch in C++ Perplexity AI: From Its Use To Operation, Everything You Need To Know About Google's Newest Challenger The Pirate Bay was recently down for over a week due to a DDoS attack How to Build 600+ Links in One Month provided by Google News Machine learning data pipeline outfit Splice Machine files for insolvency Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ... Distributed SQL System Review: Snowflake vs Splice Machine Splice Machine Launches Feature Store to Simplify Feature Engineering Splice Machine scores $15M to make Hadoop run in real time provided by Google News Tarantool Announces New Enterprise Version With Enhanced Scaling and Monitoring Capabilities 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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